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爱可可老师一周论文精选

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No 1. 《The Matrix Calculus You Need For Deep Learning》
No 2. 《Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs》
No 3. 《Fusion++: Volumetric Object-Level SLAM》
No 4. 【用深度学习预测大地震余震】
No 5. 《Multi-dimensional Graph Convolutional Networks》
No 6. 《Pairwise Relational Networks for Face Recognition》
No 7. 《R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos》
No 8. 《Wasserstein is all you need》
No 9. 《Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures》
No 10. 《Convolutional Neural Networks with Recurrent Neural Filters》
No 11. 《Support Neighbor Loss for Person Re-Identification》
No 12. 《Gaussian Word Embedding with a Wasserstein Distance Loss》
No 13. 《Generalisation in humans and deep neural networks》
No 14. 《Generating Text through Adversarial Training using Skip-Thought Vectors》
No 15. 《An elementary introduction to information geometry》
No 16. 《Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model》
No 17. 《Simultaneous Localization And Mapping with depth Prediction using Capsule Networks for UAVs》
No 18. 《Learning Neural Templates for Text Generation》
No 19. 《Graph Edit Distance Computation via Graph Neural Networks》
No 20. 《Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models》
No 21. 《FPGA Implementation of Convolutional Neural Networks with Fixed-Point Calculations》
No 22. 《Deep Reinforcement Learning in Portfolio Management》
No 23. 《On Tree-Based Neural Sentence Modeling》
No 24. 《Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning》
No 25. 《On Deep Neural Networks for Detecting Heart Disease》
No 26. 《Importance Weighting and Varational Inference》
No 27. 《SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning》
No 28. 《Unknown Examples & Machine Learning Model Generalization》
No 29. 《Can 3D Pose be Learned from 2D Projections Alone?》
No 30. 《Cross-view image synthesis using geometry-guided conditional GANs》
No 31. 《A Unified Analysis of Stochastic Momentum Methods for Deep Learning》
No 32. 《Adversarial Sampling for Active Learning》
No 33. 《DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN》
No 34. 《Medical Image Imputation from Image Collections》
No 35. 《Linguistic data mining with complex networks: a stylometric-oriented approach》
No 36. 《Metric Learning for Novelty and Anomaly Detection》
No 37. 《The Scientific Prize Network Predicts Who Pushes the Boundaries of Science》
No 38. 《Bayesian Hidden Markov Tree Models for Clustering Genes with Shared Evolutionary History》
No 39. 《Deep Learning for Energy Markets》
No 40. 《Learning to Compare: Relation Network for Few-Shot Learning》
No 41. 《What Makes Reading Comprehension Questions Easier?》
No 42. 《Use Of Vapnik-Chervonenkis Dimension in Model Selection》
No 43. 《BlockQNN: Efficient Block-wise Neural Network Architecture Generation》
No 44. 《Approximation Trees: Statistical Stability in Model Distillation》
No 45. 《Conceptual Domain Adaptation Using Deep Learning》
No 46. 《Ontology Reasoning with Deep Neural Networks》
No 47. 《DeepDownscale: a Deep Learning Strategy for High-Resolution Weather Forecast》
No 48. 《Improving Abstraction in Text Summarization》
No 49. 《Spectral-Pruning: Compressing deep neural network via spectral analysis》
No 50. 《Revisiting Character-Based Neural Machine Translation with Capacity and Compression》

No 1. 《Notes on Deep Learning for NLP》
No 2. 《Bilinear Attention Networks》
No 3. 《PythonRobotics: a Python code collection of robotics algorithms》
No 4. 《Twin-GAN -- Unpaired Cross-Domain Image Translation with Weight-Sharing GANs》
No 5. 《Towards Effective Deep Embedding for Zero-Shot Learning》
No 6. 《Open Set Chinese Character Recognition using Multi-typed Attributes》
No 7. 《AAD: Adaptive Anomaly Detection through traffic surveillance videos》
No 8. 《Probabilistic Model of Object Detection Based on Convolutional Neural Network》
No 9. 《Deep Lidar CNN to Understand the Dynamics of Moving Vehicles》
No 10. 《A Tree-based Decoder for Neural Machine Translation》
No 11. 《APES: a Python toolbox for simulating reinforcement learning environments》
No 12. 《Bottom-Up Abstractive Summarization》
No 13. 《Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I》
No 14. 《Total Recall: Understanding Traffic Signs using Deep Hierarchical Convolutional Neural Networks》
No 15. 《Reinforcement Learning for Relation Classification from Noisy Data》
No 16. 《Hyperbolic Recommender Systems》
No 17. 《Retrieve-and-Read: Multi-task Learning of Information Retrieval and Reading Comprehension》
No 18. 《Learning Neural Templates for Text Generation》
No 19. 《Iterative Recursive Attention Model for Interpretable Sequence Classification》
No 20. 《Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text》
No 21. 《Social Network Structure is Predictive of Health and Wellness》
No 22. 《ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions》
No 23. 《Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI》
No 24. 《Interpretation of Natural Language Rules in Conversational Machine Reading》
No 25. 《Multi-Hop Knowledge Graph Reasoning with Reward Shaping》
No 26. 《Dense Pose Transfer》
No 27. 《A Unified Analysis of Stochastic Momentum Methods for Deep Learning》
No 28. 《Choosing How to Choose Papers》
No 29. 《Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization》
No 30. 《Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks》

No 1. 《Deep learning for time series classification: a review》
No 2. 《Deep Learning for Generic Object Detection: A Survey》
No 3. 《Data Dropout: Optimizing Training Data for Convolutional Neural Networks》
No 4. 《Semantic Instance Segmentation with a Discriminative Loss Function》
No 5. 【ECCV 2018 Best Paper Award】
No 6. 《Group Normalization》
No 7. 《Semi-supervised Learning on Graphs with Generative Adversarial Nets》
No 8. 《Hyperbolic Recommender Systems》
No 9. 《Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?》
No 10. 《Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I》
No 11. 《Bayesian Convolutional Neural Networks》
No 12. 【端到端几何推理发现潜在3D锚点】
No 13. 《Dense Pose Transfer》
No 14. 《PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track》
No 15. 《TVQA: Localized, Compositional Video Question Answering》
No 16. 《Searching for Efficient Multi-Scale Architectures for Dense Image Prediction》
No 17. 《Embedding Logical Queries on Knowledge Graphs》
No 18. 《An Analysis of Hierarchical Text Classification Using Word Embeddings》
No 19. 《ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks》
No 20. 《Bayesian Semi-supervised Learning with Graph Gaussian Processes》
No 21. 《Five lessons from building a deep neural network recommender》
No 22. 《Learning to Describe Differences Between Pairs of Similar Images》
No 23. 《Learning Sequence Encoders for Temporal Knowledge Graph Completion》
No 24. 《Spherical Latent Spaces for Stable Variational Autoencoders》
No 25. 《Entropy and Graph Energy of Complex Networks》
No 26. 《GANimation: Anatomically-aware Facial Animation from a Single Image》
No 27. 《Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?》
No 28. 《Bayesian Nonparametric Spectral Estimation》
No 29. 《Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks》
No 30. 《Combined Reinforcement Learning via Abstract Representations》

No 1. 《Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection》
No 2. 《Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction》
No 3. 《Random Warping Series: A Random Features Method for Time-Series Embedding》
No 4. 《Faster RER-CNN: application to the detection of vehicles in aerial images》
No 5. 《Human activity recognition based on time series analysis using U-Net》
No 6. 《Deep Clustering for Unsupervised Learning of Visual Features》
No 7. 《Deep Graph Infomax》
No 8. 《Why scatter plots suggest causality, and what we can do about it》
No 9. 《Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding》
No 10. 《Real-Time Monocular Object-Model Aware Sparse SLAM》
No 11. 《No Multiplication? No Floating Point? No Problem! Training Networks for Efficient Inference》
No 12. 《PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume》
No 13. 《A Survey of Learning Causality with Data: Problems and Methods》
No 14. 《On Reinforcement Learning for Full-length Game of StarCraft》
No 15. 《Combined convolutional and recurrent neural networks for hierarchical classification of images》
No 16. 《Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data》
No 17. 【深度学习高精度基因组研究】
No 18. 《VoxelMorph: A Learning Framework for Deformable Medical Image Registration》
No 19. 《LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking》
No 20. 《RPNet: an End-to-End Network for Relative Camera Pose Estimation》
No 21. 《Night-to-Day Image Translation for Retrieval-based Localization》
No 22. 《Multi-View Community Detection in Facebook Public Pages》
No 23. 《Active Anomaly Detection via Ensembles》
No 24. 《Learning to Address Health Inequality in the United States with a Bayesian Decision Network》
No 25. 《A Survey on Theoretical Advances of Community Detection in Networks》
No 26. 《Semi-Supervised Sequence Modeling with Cross-View Training》
No 27. 《WaveCycleGAN: Synthetic-to-natural speech waveform conversion using cycle-consistent adversarial networks》
No 28. 《Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation》
No 29. 《Understanding Fake Faces》
No 30. 《Sparsified SGD with Memory》

No 1. 【Airbnb动态定价的定制回归模型】
No 2. 《Real-time 3D Pose Estimation with a Monocular Camera Using Deep Learning and Object Priors On an Autonomous Racecar》
No 3. 《Taming VAEs》
No 4. 《Deep Graph Infomax》
No 5. 《An Introduction to Probabilistic Programming》
No 6. 《How Powerful are Graph Neural Networks?》
No 7. 《Multitask Learning on Graph Neural Networks - Learning Multiple Graph Centrality Measures with a Unified Network》
No 8. 《Global Weighted Average Pooling Bridges Pixel-level Localization and Image-level Classification》
No 9. 《AI Benchmark: Running Deep Neural Networks on Android Smartphones》
No 10. 《Non-local Neural Networks》
No 11. 《Object Detection from Scratch with Deep Supervision》
No 12. 《Combined Image- and World-Space Tracking in Traffic Scenes》
No 13. 《Graph Convolution over Pruned Dependency Trees Improves Relation Extraction》
No 14. 《Learning with Random Learning Rates》
No 15. 《Night-to-Day Image Translation for Retrieval-based Localization》
No 16. 《Unsupervised Person Image Synthesis in Arbitrary Poses》
No 17. 《LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking》
No 18. 《WaveCycleGAN: Synthetic-to-natural speech waveform conversion using cycle-consistent adversarial networks》
No 19. 《Semantic WordRank: Generating Finer Single-Document Summarizations》
No 20. 《A theoretical framework for deep locally connected ReLU network》
No 21. 《Adversarial Attacks and Defences: A Survey》
No 22. 《R-C3D: Region Convolutional 3D Network for Temporal Activity Detection》
No 23. 《Multi-Scale Fully Convolutional Network for Cardiac Left Ventricle Segmentation》
No 24. 《Over-Optimization of Academic Publishing Metrics: Observing Goodhart's Law in Action》
No 25. 《Compressing the Input for CNNs with the First-Order Scattering Transform》
No 26. 《HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering》
No 27. 《Robustness Guarantees for Bayesian Inference with Gaussian Processes》
No 28. 《Dropout Distillation for Efficiently Estimating Model Confidence》
No 29. 《Generative Ensembles for Robust Anomaly Detection》
No 30. 《CPDist: Deep Siamese Networks for Learning Distances Between Structured Preferences》

No 1. 【有助于 科学家 提高写作效率 的 十条简单规则】
No 2. 【今日焦点:Google刷新多项NLP任务的BERT模型】
No 3. 《Unsupervised Learning via Meta-Learning》
No 4. 【RecSys2018 Best Long Paper Award:因果嵌入推荐算法】
No 5. 《Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime》
No 6. 《Multi-Task Learning as Multi-Objective Optimization》
No 7. 《Deep convolutional Gaussian processes》
No 8. 《FashionNet: Personalized Outfit Recommendation with Deep Neural Network》
No 9. 《A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models》
No 10. 《Generative Adversarial Active Learning for Unsupervised Outlier Detection》
No 11. 《Deep clustering: On the link between discriminative models and K-means》
No 12. 《A Multi-Face Challenging Dataset for Robust Face Recognition》
No 13. 《ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design》
No 14. 《Learning to Remember, Forget and Ignore using Attention Control in Memory》
No 15. 《Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs》
No 16. 《Deep processing of structured data》
No 17. 《Training Complex Models with Multi-Task Weak Supervision》
No 18. 《Principal component-guided sparse regression》
No 19. 【用强化学习改进智能体设计】
No 20. 《Projective Inference in High-dimensional Problems: Prediction and Feature Selection》
No 21. 《Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes》
No 22. 《Analyzing the Noise Robustness of Deep Neural Networks》
No 23. 《GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration》
No 24. 《The Laplacian in RL: Learning Representations with Efficient Approximations》
No 25. 《DeSIGN: Design Inspiration from Generative Networks》
No 26. 【离策略评价估计器设计】
No 27. 《Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks》
No 28. 《The Blackbird Dataset: A large-scale dataset for UAV perception in aggressive flight》
No 29. 《Interpreting Adversarial Robustness: A View from Decision Surface in Input Space》
No 30. 《Sanity Checks for Saliency Maps》

No 1. 晚安~
No 2. 没错了~ [笑cry] ​
No 3. 【基于PyTorch的开源医学图像处理框架,提供全套的医学成像载入、预处理模块和数据集】
No 4. 原来是这样,很棒的设计! ​
No 5. 可视化:各个国家的真正大小 src:http://t.cn/E79bUpF ​...
No 6. 《计算机程序的构造和解释》
No 7. 【(Python)PDF表格数据提取库(提供命令行工具)】
No 8. 《Revisiting RCNN: On Awakening the Classification Power of Faster RCNN》
No 9.
No 10. 【(Python)计算机视觉研究基础库】
No 11. 小盆友:“哇!你3D打印了一个‘保存’图标!”
No 12. 【Word学术写作指南】
No 13. 2018进度:▓▓▓▓▓▓▓▓▓▓▓▓░░░ 78% ​...
No 14. 【开源目标检测工具包(PyTorch)】
No 15. [偷笑] ​
No 16. 'BiLSTM-CNN-CRF tagger' by Artem Chernodub GitHub:...
No 17. 【今日焦点:Google刷新多项NLP任务的BERT模型】
No 18. 早! [太阳] ​
No 19. 和狗狗时隔三年重聚的感人时刻 😭 http://t.cn/E79nRhv ​...
No 20. 今天数学深渊那张图,让不少盆友想起了AI深渊这张图,翻出来大家回味回味...
No 21. 【新手试炼:机器学习股市预测】
No 22. 【Python高级应用程序与仪表板解决方案,可整合Bokeh,Matplotlib,HoloViews和其他Python绘图库的交互可视化】
No 23. 【深度学习在转移性乳腺癌检测中的应用】
No 24. 十足科幻风:开上纽约街头的NASA新款火星探测车 [笑而不语] http://t.cn/E7C5w2...
No 25. 【斯坦福机器学习课程“CS 229 - Machine Learning”速查表(中文版)】
No 26. 【开源神经网络机器翻译框架OpenNMT的Python实现】
No 27. 【车牌识别API(云服务)】
No 28. 【异常检测学习资源大列表】
No 29. Boss vs. Leader [思考] ​
No 30. 还真是 [笑cry] ​
No 31. 【R语言机器学习入门】
No 32. 《2080 Ti TensorFlow GPU benchmarks - 2080 Ti vs V100 vs 1080 Ti vs Titan V》
No 33. 【spaCy自然语言处理实例指南】
No 34. 【根据平面画像合成3D头发】
No 35. 【MD.ai医学成像深度学习课程资料】
No 36. 《The Way to Go》
No 37. 【不寻常的自编码器】
No 38. 《Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes》
No 39. 微积分速查 ​
No 40. 《算法工程师手册(数学基础/统计学习/深度学习/自然语言处理/计算机视觉/工具)》
No 41. 【未来的AI产品:设计愈加复杂使用愈加简单】
No 42. 笑容逐渐舒展 [笑cry] ​
No 43. 波士顿动力最新发布的Atlas机器人跳台阶视频:控制软件使用包括腿部、手臂和躯干在内的整个身体来调整...
No 44. 【深度学习语义分割概览】
No 45. 《Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation》
No 46. 【基于网页的图像标注工具】
No 47. 【Python封装的Google Tesseract文字识别】
No 48. 'OpenCV-Python-Tutorial 中文版' by No War GitHub: htt...
No 49. 《End-to-End Content and Plan Selection for Data-to-Text Generation》
No 50. 《Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour》

No 1. 【Matplotlib终极指南】
No 2. 《Single-shot real-time femtosecond imaging of temporal focusing》
No 3. 【纯用NumPy实现神经网络】
No 4. ❤️ http://t.cn/E7jQOXU
No 5. 警惕所有不提具体任务和数据集、鼓吹“AI(再次/全面)超越人类”
No 6. 【用Python/Geopandas/Matplotlib创建gif地图图片】
No 7. 笑容逐渐舒展 [笑cry] ​
No 8. 【异常检测学习资源大列表】
No 9. Boss vs. Leader [思考] ​
No 10. 无监督学习 [哈哈] src:http://t.cn/E7HG0E9 ​...
No 11. 【GAN的理解与优化】
No 12. 【熵:不确定性度量——八个属性,几个例子和一个定理】
No 13. 【新手试炼:机器学习股市预测】
No 14. 《The Way to Go》
No 15. 【基于网页的图像标注工具】
No 16. 🐰[哈哈] http://t.cn/E7jR1J4
No 17. 【MD.ai医学成像深度学习课程资料】
No 18. 【数据科学家最需要的技能】
No 19. 最近医疗领域深度网络论文大爆发,需要冷静思考:算法验证 ≠ 临床有效性
No 20. 值得AI研究人员思考的街头涂鸦 [思考] ​...
No 21. 【深度网络与展望:视觉和机器学习】
No 22. 【辛普森的悖论:如何用相同的数据证明相反的论点】
No 23. 【生命之树:生物演化关系示意图,不同半径的扇形代表时间的演进,每个树杈的端点代表一类生物的灭亡】
No 24. 《**和美国谁能成人工智能领域的领军者? - 知乎》
No 25. #可可家训# 学会发现和欣赏,愉悦会源源而来;小心痴迷、嫉妒和占有的欲望,懊悔、痛苦和悲伤多源于此。...
No 26. 光雕投影(Projection mapping):也称为立体光雕,是一种投影技术,可以将物体(多半是...
No 27. think vs. plan vs. execute [思考] ​
No 28. 【Python封装的Google Tesseract文字识别】
No 29. 晚安~
No 30. 没错了~ [笑cry] ​
No 31. 【Python高级应用程序与仪表板解决方案,可整合Bokeh,Matplotlib,HoloViews和其他Python绘图库的交互可视化】
No 32. Google AI Research的Repo,目前包括(后续应该会发布BERT代码):- man...
No 33. 《FaceBoxes: A CPU Real-time Face Detector with High Accuracy》
No 34. 【TensorFlow的简单易用课程】
No 35. 【nuScenes无人驾驶数据集开发工具集】
No 36. 【基于PyTorch的开源医学图像处理框架,提供全套的医学成像载入、预处理模块和数据集】
No 37. 猎豹尾巴在高速过弯时的用途 http://t.cn/E7Hcnch ​...
No 38. 【(Python)计算机视觉研究基础库】
No 39. #今日发呆专用# ​
No 40. ANYmal:专注协作的“跟班”
No 41. PyTorch Implementation by lxg2015 GitHub:http://t....
No 42. 出个面试题:请问从机器学习角度看这段视频说明什么? http://t.cn/E7Hx5O6 ​...
No 43. 《Network Distance Based on Laplacian Flows on Graphs》
No 44. 《Reinforcement Learning for Relation Classification from Noisy Data》
No 45. 原来是这样,很棒的设计! ​
No 46. 【实体识别数据集集锦】
No 47. 【Keras-MXNet】
No 48. 【Binder 2.0技术指南】
No 49. 【OpenAI Gym推箱子游戏环境】
No 50. 早! [太阳] ​

No 1. 【Matplotlib终极指南】
No 2. 《Single-shot real-time femtosecond imaging of temporal focusing》
No 3. 【纯用NumPy实现神经网络】
No 4. ❤️ http://t.cn/E7jQOXU
No 5. 警惕所有不提具体任务和数据集、鼓吹“AI(再次/全面)超越人类”
No 6. 【用Python/Geopandas/Matplotlib创建gif地图图片】
No 7. 笑容逐渐舒展 [笑cry] ​
No 8. 【异常检测学习资源大列表】
No 9. Boss vs. Leader [思考] ​
No 10. 无监督学习 [哈哈] src:http://t.cn/E7HG0E9 ​...
No 11. 【GAN的理解与优化】
No 12. 【熵:不确定性度量——八个属性,几个例子和一个定理】
No 13. 【新手试炼:机器学习股市预测】
No 14. 《The Way to Go》
No 15. 【基于网页的图像标注工具】
No 16. 🐰[哈哈] http://t.cn/E7jR1J4
No 17. 【MD.ai医学成像深度学习课程资料】
No 18. 【数据科学家最需要的技能】
No 19. 最近医疗领域深度网络论文大爆发,需要冷静思考:算法验证 ≠ 临床有效性
No 20. 值得AI研究人员思考的街头涂鸦 [思考] ​...
No 21. 【深度网络与展望:视觉和机器学习】
No 22. 【辛普森的悖论:如何用相同的数据证明相反的论点】
No 23. 【生命之树:生物演化关系示意图,不同半径的扇形代表时间的演进,每个树杈的端点代表一类生物的灭亡】
No 24. 《**和美国谁能成人工智能领域的领军者? - 知乎》
No 25. #可可家训# 学会发现和欣赏,愉悦会源源而来;小心痴迷、嫉妒和占有的欲望,懊悔、痛苦和悲伤多源于此。...
No 26. 光雕投影(Projection mapping):也称为立体光雕,是一种投影技术,可以将物体(多半是...
No 27. think vs. plan vs. execute [思考] ​
No 28. 【Python封装的Google Tesseract文字识别】
No 29. 晚安~
No 30. 没错了~ [笑cry] ​
No 31. 【Python高级应用程序与仪表板解决方案,可整合Bokeh,Matplotlib,HoloViews和其他Python绘图库的交互可视化】
No 32. Google AI Research的Repo,目前包括(后续应该会发布BERT代码):- man...
No 33. 《FaceBoxes: A CPU Real-time Face Detector with High Accuracy》
No 34. 【TensorFlow的简单易用课程】
No 35. 【nuScenes无人驾驶数据集开发工具集】
No 36. 【基于PyTorch的开源医学图像处理框架,提供全套的医学成像载入、预处理模块和数据集】
No 37. 猎豹尾巴在高速过弯时的用途 http://t.cn/E7Hcnch ​...
No 38. 【(Python)计算机视觉研究基础库】
No 39. #今日发呆专用# ​
No 40. ANYmal:专注协作的“跟班”
No 41. PyTorch Implementation by lxg2015 GitHub:http://t....
No 42. 出个面试题:请问从机器学习角度看这段视频说明什么? http://t.cn/E7Hx5O6 ​...
No 43. 《Network Distance Based on Laplacian Flows on Graphs》
No 44. 《Reinforcement Learning for Relation Classification from Noisy Data》
No 45. 原来是这样,很棒的设计! ​
No 46. 【实体识别数据集集锦】
No 47. 【Keras-MXNet】
No 48. 【Binder 2.0技术指南】
No 49. 【OpenAI Gym推箱子游戏环境】
No 50. 早! [太阳] ​

No 1. 《Meta-Learning: A Survey》
No 2. 【有助于 科学家 提高写作效率 的 十条简单规则】
No 3. 《Variational Bayesian Monte Carlo》
No 4. 《The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models》
No 5. 《Poincaré GloVe: Hyperbolic Word Embeddings》
No 6. 《Trellis Networks for Sequence Modeling》
No 7. 《Piano Genie》
No 8. 《Deep Learning for Image Denoising: A Survey》
No 9. 《Sequential Learning of Movement Prediction in Dynamic Environments using LSTM Autoencoder》
No 10. 《Training convolutional neural networks with megapixel images》
No 11. 《Rethinking the Value of Network Pruning》
No 12. 《Adversarial Text Generation Without Reinforcement Learning》
No 13. 《Discriminator Rejection Sampling》
No 14. 《Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications》
No 15. 《Dual Convolutional Neural Network for Graph of Graphs Link Prediction》
No 16. 《Generation Meets Recommendation: Proposing Novel Items for Groups of Users》
No 17. 《Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things》
No 18. 《Q-map: a Convolutional Approach for Goal-Oriented Reinforcement Learning》
No 19. 《Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences》
No 20. 《Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks》
No 21. 《SFV: Reinforcement Learning of Physical Skills from Videos》
No 22. 《A Gentle Introduction to Deep Learning in Medical Image Processing》
No 23. 《Realistic Adversarial Examples in 3D Meshes》
No 24. 《Fast deep reinforcement learning using online adjustments from the past》
No 25. 《Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron》
No 26. 《First-order and second-order variants of the gradient descent: a unified framework》
No 27. 《Good Initializations of Variational Bayes for Deep Models》
No 28. 《Gradient Agreement as an Optimization Objective for Meta-Learning》
No 29. 《Deep Imitative Models for Flexible Inference, Planning, and Control》
No 30. 《Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding》

No 1. 《A Novel Domain Adaptation Framework for Medical Image Segmentation》
No 2. 《Do Deep Generative Models Know What They Don't Know?》
No 3. 《Deep Learning for Image Denoising: A Survey》
No 4. 《A Social Network Analysis of Articles on Social Network Analysis》
No 5. 《Model Selection Techniques -- An Overview》
No 6. 【今日焦点:Google刷新多项NLP任务的BERT模型】
No 7. 《MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects》
No 8. 《Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach》
No 9. 《Interpretable LSTMs For Whole-Brain Neuroimaging Analyses》
No 10. 《Deep Graph Convolutional Encoders for Structured Data to Text Generation》
No 11. 《Deep Learning with the Random Neural Network and its Applications》
No 12. 《Neighbourhood Consensus Networks》
No 13. 《DGC-Net: Dense Geometric Correspondence Network》
No 14. 《On the Margin Theory of Feedforward Neural Networks》
No 15. 《A Gentle Introduction to Deep Learning in Medical Image Processing》
No 16. 《Applying Deep Learning To Airbnb Search》
No 17. 《Recipe1M: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images》
No 18. 《Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations》
No 19. 《Person Retrieval in Surveillance Video using Height, Color and Gender》
No 20. 《Fast deep reinforcement learning using online adjustments from the past》
No 21. 《Contextual Topic Modeling For Dialog Systems》
No 22. 《Gradient Agreement as an Optimization Objective for Meta-Learning》
No 23. 《Good Initializations of Variational Bayes for Deep Models》
No 24. 《First-order and second-order variants of the gradient descent: a unified framework》
No 25. 《Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing》
No 26. 《Image Inpainting for Irregular Holes Using Partial Convolutions》
No 27. 《Neural Network Models for Natural Language Inference Fail to Capture the Semantics of Inference》
No 28. 《Image Super-Resolution Using VDSR-ResNeXt and SRCGAN》
No 29. 《From Louvain to Leiden: guaranteeing well-connected communities》
No 30. 《LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild》

No 1. 《You May Not Need Attention》
No 2. 《Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training》
No 3. 《GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks》
No 4. 《pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference》
No 5. 《Towards Efficient Large-Scale Graph Neural Network Computing》
No 6. 《Sequence classification with human attention》
No 7. 《Dynamic Graph Neural Networks》
No 8. 《CartoonGAN: Generative Adversarial Networks for Photo Cartoonization》
No 9. 《LadderNet: Multi-path networks based on U-Net for medical image segmentation》
No 10. 《WaveGlow: A Flow-based Generative Network for Speech Synthesis》
No 11. 《CatBoost: gradient boosting with categorical features support》
No 12. 《DropBlock: A regularization method for convolutional networks》
No 13. 《Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning》
No 14. 《Graph Convolutional Reinforcement Learning for Multi-Agent Cooperation》
No 15. 《Differentiable MPC for End-to-end Planning and Control》
No 16. 《Understanding Deep Convolutional Networks through Gestalt Theory》
No 17. 《Learning Material-Aware Local Descriptors for 3D Shapes》
No 18. 《Textbook Question Answering with Knowledge Graph Understanding and Unsupervised Open-set Text Comprehension》
No 19. 《Humans are still the best lossy image compressors》
No 20. 《A Comparative Study of Fruit Detection and Counting Methods for Yield Mapping in Apple Orchards》
No 21. 《Local Homology of Word Embeddings》
No 22. 《Super-pixel cloud detection using Hierarchical Fusion CNN》
No 23. 《Audio to Body Dynamics》
No 24. 《The Wasserstein transform》
No 25. 《Reversible Recurrent Neural Networks》
No 26. 《Recycle-GAN: Unsupervised Video Retargeting》
No 27. 《A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures》
No 28. 《Communities as Well Separated Subgraphs With Cohesive Cores: Identification of Core-Periphery Structures in Link Communities》
No 29. 《Automatic differentiation in ML: Where we are and where we should be going》
No 30. 《Dilated DenseNets for Relational Reasoning》

No 1. 《The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale》
No 2. 《Face Recognition: From Traditional to Deep Learning Methods》
No 3. 《WaveGlow: A Flow-based Generative Network for Speech Synthesis》
No 4. 《You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization》
No 5. 《Language GANs Falling Short》
No 6. 《How deep is deep enough? - Optimizing deep neural network architecture》
No 7. 《Named Entity Disambiguation using Deep Learning on Graphs》
No 8. 《Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks》
No 9. 《Multi-level Memory for Task Oriented Dialogs》
No 10. 《Modeling Attention Flow on Graphs》
No 11. 《Towards Explainable NLP: A Generative Explanation Framework for Text Classification》
No 12. 《Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension》
No 13. 《Neural Nearest Neighbors Networks》
No 14. 《Do RNNs learn human-like abstract word order preferences?》
No 15. 《Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells》
No 16. 《Simple, Distributed, and Accelerated Probabilistic Programming》
No 17. 《An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution》
No 18. 《Textbook Question Answering with Knowledge Graph Understanding and Unsupervised Open-set Text Comprehension》
No 19. 《Content Selection in Deep Learning Models of Summarization》
No 20. 《How the fundamental concepts of mathematics and physics explain deep learning》
No 21. 《Stochastic Neighbor Embedding under f-divergences》
No 22. 《Towards continual learning in medical imaging》
No 23. 《Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach》
No 24. 《Multi-Agent Common Knowledge Reinforcement Learning》
No 25. 《Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy》
No 26. 《Multiple-Attribute Text Style Transfer》
No 27. 《Scalable Deep kk-Subspace Clustering》
No 28. 《Dilated DenseNets for Relational Reasoning》
No 29. 《You May Not Need Attention》
No 30. 《Finding Mixed Nash Equilibria of Generative Adversarial Networks》

No 1. 《YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers》
No 2. 《Gradient Descent Finds Global Minima of Deep Neural Networks》
No 3. 《DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution》
No 4. 《Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks》
No 5. 《Understanding Back-Translation at Scale》
No 6. 《Online Embedding Compression for Text Classification using Low Rank Matrix Factorization》
No 7. 《ImageNet/ResNet-50 Training in 224 Seconds》
No 8. 《Measuring the Effects of Data Parallelism on Neural Network Training》
No 9. 《A Survey on Data Collection for Machine Learning: a Big Data - AI Integration Perspective》
No 10. 《The Price of Fair PCA: One Extra Dimension》
No 11. 《CariGANs: Unpaired Photo-to-Caricature Translation》
No 12. 《Building a Winning Self-Driving Car in Six Months》
No 13. 《Stochastic Normalizations as Bayesian Learning》
No 14. 《Unsupervised image segmentation via maximum a posteriori estimation of continuous max-flow》
No 15. 《Dial2Desc: End-to-end Dialogue Description Generation》
No 16. 《Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning》
No 17. 《Sorting out Lipschitz function approximation》
No 18. 《Bias and Generalization in Deep Generative Models: An Empirical Study》
No 19. 《ExGate: Externally Controlled Gating for Feature-based Attention in Artificial Neural Networks》
No 20. 《Survey on Vision-based Path Prediction》
No 21. 《Neural Music Synthesis for Flexible Timbre Control》
No 22. 《Scale-variant topological information for characterizing complex networks》
No 23. 《Confusion2Vec: Towards Enriching Vector Space Word Representations with Representational Ambiguities》
No 24. 《Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series》
No 25. 《Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling》
No 26. 《Mesh-TensorFlow: Deep Learning for Supercomputers》
No 27. 《VIREL: A Variational Inference Framework for Reinforcement Learning》
No 28. 《Learning Two Layer Rectified Neural Networks in Polynomial Time》
No 29. 《A Review of automatic differentiation and its efficient implementation》
No 30. 《Exposing DeepFake Videos By Detecting Face Warping Artifacts》

No 1. 《Rethinking ImageNet Pre-training》
No 2. 《YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers》
No 3. 《Orthographic Feature Transform for Monocular 3D Object Detection》
No 4. 《Learning From Positive and Unlabeled Data: A Survey》
No 5. 《Sampling Can Be Faster Than Optimization》
No 6. 《Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection》
No 7. 《Stochastic Deep Networks》
No 8. 《An Introductory Survey on Attention Mechanisms in NLP Problems》
No 9. 《Improving Multi-Person Pose Estimation using Label Correction》
No 10. 《Understanding and Predicting Links in Graphs: A Persistent Homology Perspective》
No 11. 《A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data》
No 12. 《Explaining Deep Learning Models - A Bayesian Non-parametric Approach》
No 13. 《ImageNet/ResNet-50 Training in 224 Seconds》
No 14. 《Forecasting People's Needs in Hurricane Events from Social Network》
No 15. 《Deep Q learning for fooling neural networks》
No 16. 《Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification》
No 17. 《Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?》
No 18. 《Pitfalls of Graph Neural Network Evaluation》
No 19. 《Interactive dimensionality reduction using similarity projections》
No 20. 《Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving》
No 21. 《Co-Representation Learning For Classification and Novel Class Detection via Deep Networks》
No 22. 《Bayesian variational inference for exponential random graph models》
No 23. 《Doc2Im: document to image conversion through self-attentive embedding》
No 24. 《NEMGAN: Noise Engineered Mode-matching GAN》
No 25. 《Language GANs Falling Short》
No 26. 《Modular Architecture for StarCraft II with Deep Reinforcement Learning》
No 27. 《A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks》
No 28. 《Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks》
No 29. 《Image Classification at Supercomputer Scale》
No 30. 《The relativistic discriminator: a key element missing from standard GAN》

No 1. 【基因组学深度学习入门】
No 2. 【新任务&数据集:视觉常识推理(VCR)】
No 3. 《Smooth Loss Functions for Deep Top-k Classification》
No 4. 《Dataset Distillation》
No 5. 《Weakly Supervised Semantic Image Segmentation with Self-correcting Networks》
No 6. 【用于视频超分辨率的时间相干GAN(TecoGAN)】
No 7. 《Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector》
No 8. 《How Many Samples are Needed to Learn a Convolutional Neural Network?》
No 9. 《Do GAN Loss Functions Really Matter?》
No 10. 《Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos》
No 11. 《One-Shot Instance Segmentation》
No 12. 《ML-Net: multi-label classification of biomedical texts with deep neural networks》
No 13. 《Partial Convolution based Padding》
No 14. 《Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving》
No 15. 《DynamicGEM: A Library for Dynamic Graph Embedding Methods》
No 16. 《Matching Features without Descriptors: Implicitly Matched Interest Points (IMIPs)》
No 17. 《Perturbative Neural Networks》
No 18. 《Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models》
No 19. 【人形机器人分级视觉运动控制】
No 20. 《Guiding the One-to-one Mapping in CycleGAN via Optimal Transport》
No 21. 《Scalable Logo Recognition using Proxies》
No 22. 《Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting》
No 23. 《Exploiting Sentence Embedding for Medical Question Answering》
No 24. 《An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss》
No 25. 《Understanding the impact of entropy in policy learning》
No 26. 《A Sufficient Condition for Convergences of Adam and RMSProp》
No 27. 《Sentence Encoding with Tree-constrained Relation Networks》
No 28. 《LinkNet: Relational Embedding for Scene Graph》
No 29. 《Is Data Clustering in Adversarial Settings Secure?》
No 30. 《Understanding and Measuring Psychological Stress using Social Media》

No 1. 《An Introduction to Deep Reinforcement Learning》
No 2. 《Graph-Based Global Reasoning Networks》
No 3. 《Deformable ConvNets v2: More Deformable, Better Results》
No 4. 《Are All Training Examples Created Equal? An Empirical Study》
No 5. 《The Graph-based Broad Behavior-Aware Recommendation System for Interactive News》
No 6. 《Measure, Manifold, Learning, and Optimization: A Theory Of Neural Networks》
No 7. 《ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness》
No 8. 《Optimal Algorithms for Non-Smooth Distributed Optimization in Networks》
No 9. 【视图先验学习单视图3D重建】
No 10. 《Metropolis-Hastings Generative Adversarial Networks》
No 11. 《ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware》
No 12. 《GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism》
No 13. 《Distinguishing correlation from causation using genome-wide association studies》
No 14. 《Learning 3D Human Dynamics from Video》
No 15. 《Neural Ordinary Differential Equations》
No 16. 《Pitfalls of Graph Neural Network Evaluation》
No 17. 《Understanding Unequal Gender Classification Accuracy from Face Images》
No 18. 《Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs》
No 19. 《Iterative Transformer Network for 3D Point Cloud》
No 20. 《Macro action selection with deep reinforcement learning in StarCraft》
No 21. 《A survey of large-scale reasoning on the Web of data》
No 22. 《Unsupervised Word Discovery with Segmental Neural Language Models》
No 23. 《Seeing in the dark with recurrent convolutional neural networks》
No 24. 《Fashion-Gen: The Generative Fashion Dataset and Challenge》
No 25. 《Multifidelity Approximate Bayesian Computation》
No 26. 《Scan2CAD: Learning CAD Model Alignment in RGB-D Scans》
No 27. 《Multivariate Forecasting of Crude Oil Spot Prices using Neural Networks》
No 28. 《Learning to Reason with Third-Order Tensor Products》
No 29. 《Learning Finite State Representations of Recurrent Policy Networks》
No 30. 《From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec》

No 1. 《Deep Learning on Graphs: A Survey》
No 2. 《ShelfNet for Real-time Semantic Segmentation》
No 3. 《Recent Advances in Autoencoder-Based Representation Learning》
No 4. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》
No 5. 《Bayesian Layers: A Module for Neural Network Uncertainty》
No 6. 《Adversarial Transfer Learning》
No 7. 《Comixify: Transform video into a comics》
No 8. 《CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss》
No 9. 《Self-Improving Visual Odometry》
No 10. 《Making Classification Competitive for Deep Metric Learning》
No 11. 《Non-delusional Q-learning and value iteration》
No 12. 《A Style-Based Generator Architecture for Generative Adversarial Networks》
No 13. 【大规模AI训练:大批量(Large-Batch)训练实证研究】
No 14. 《A Compact Embedding for Facial Expression Similarity》
No 15. 《Segmentation-driven 6D Object Pose Estimation》
No 16. 《Faster Neural Networks Straight from JPEG》
No 17. 《Graph based Question Answering System》
No 18. 《GaterNet: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network》
No 19. 《SlowFast Networks for Video Recognition》
No 20. 《Flexible and Scalable State Tracking Framework for Goal-Oriented Dialogue Systems》
No 21. 《General-to-Detailed GAN for Infrequent Class Medical Images》
No 22. 《Context-Aware Synthesis and Placement of Object Instances》
No 23. 《CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks》
No 24. 《Scale-free network clustering in hyperbolic and other random graphs》
No 25. 《Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs》
No 26. 《Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning》
No 27. 《Deep-RBF Networks Revisited: Robust Classification with Rejection》
No 28. 《Cyber Anomaly Detection Using Graph-node Role-dynamics》
No 29. 《Transferring Knowledge across Learning Processes》
No 30. 《Intra-class Variation Isolation in Conditional GANs》

No 1. 《A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software》
No 2. 《基于知识图谱路径推理的可解释推荐》
No 3. 【大规模AI训练:大批量(Large-Batch)训练实证研究】
No 4. 《Bayesian Optimization in AlphaGo》
No 5. 《A Probe into Understanding GAN and VAE models》
No 6. 《A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series》
No 7. 《Hierarchical Macro Strategy Model for MOBA Game AI》
No 8. 《Graph Neural Networks: A Review of Methods and Applications》
No 9. 《PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud》
No 10. 《Understanding Individual Decisions of CNNs via Contrastive Backpropagation》
No 11. 《Multi³Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery》
No 12. 《A Tutorial on Deep Latent Variable Models of Natural Language》
No 13. 《Dynamic Network Prediction》
No 14. 《On the Dimensionality of Word Embedding》
No 15. 《Guided Zoom: Questioning Network Evidence for Fine-grained Classification》
No 16. 《Taking a Deeper Look at the Inverse Compositional Algorithm》
No 17. 《Generalized Batch Normalization: Towards Accelerating Deep Neural Networks》
No 18. 《Deep Paper Gestalt》
No 19. 《Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation》
No 20. 《Social Network Analysis: Bibliographic Network Analysis of the Field and its Evolution / Part 1. Basic Statistics and Citation Network Analysis》
No 21. 《Anomaly detection with Wasserstein GAN》
No 22. 《Geometrical Stem Detection from Image Data for Precision Agriculture》
No 23. 《SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception》
No 24. 《Provable limitations of deep learning》
No 25. 《Top-K Off-Policy Correction for a REINFORCE Recommender System》
No 26. 《AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection》
No 27. 《PyText: A Seamless Path from NLP research to production》
No 28. 《Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem》
No 29. 《Detecting rare visual relations using analogies》
No 30. 《Improved Search Strategies for Determining Facial Expression》

No 1. 《Graph Neural Networks: A Review of Methods and Applications》
No 2. 《How Powerful are Graph Neural Networks? 》
No 3. 《CFUN: Combining Faster R-CNN and U-net Network for Efficient Whole Heart Segmentation》
No 4. 《End to End Video Segmentation for Driving : Lane Detection For Autonomous Car》
No 5. 《Wikipedia2Vec: An Optimized Tool for Learning Embeddings of Words and Entities from Wikipedia》
No 6. 《Neural Approaches to Conversational AI》
No 7. 【博士论文:机器人/数据科学层次深度强化学习】
No 8. 《Can VAEs Generate Novel Examples?》
No 9. 《TextBugger: Generating Adversarial Text Against Real-world Applications》
No 10. 《Analysis Methods in Neural Language Processing: A Survey》
No 11. 《ESIR: End-to-end Scene Text Recognition via Iterative Image Rectification》
No 12. 《Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond》
No 13. 《Point Cloud GAN》
No 14. 《Learning Latent Subspaces in Variational Autoencoders》
No 15. 《Sequential Attention GAN for Interactive Image Editing via Dialogue》
No 16. 【看视频将单声道转换成2.5D 立体声的深度学习算法】
No 17. 《Pay Less Attention with Lightweight and Dynamic Convolutions》
No 18. 《The Design and Implementation of XiaoIce, an Empathetic Social Chatbot》
No 19. 《ELASTIC: Improving CNNs with Instance Specific Scaling Policies》
No 20. 《Training Deep Capsule Networks》
No 21. 【LSTM的大批量(Large-Batch)训练】
No 22. 《Machine Learning in Cyber-Security - Problems, Challenges and Data Sets》
No 23. 《Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection》
No 24. 《Modeling the Long Term Future in Model-Based Reinforcement Learning》
No 25. 《Bayesian Meta-network Architecture Learning》
No 26. 《SfMLearner++: Learning Monocular Depth & Ego-Motion using Meaningful Geometric Constraints》
No 27. 《Community structure: A comparative evaluation of community detection methods》
No 28. 《Recurrent Neural Networks with Pre-trained Language Model Embedding for Slot Filling Task》
No 29. 《Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring》
No 30. 《RegNet: Learning the Optimization of Direct Image-to-Image Pose Registration》

No 1. 【博士论文:统计与优化——统计学习算法的计算保障】
No 2. 【LSTM的大批量(Large-Batch)训练】
No 3. 【博士论文:元监督视觉学习】
No 4. 《SageDB: A Learned Database》
No 5. 《Neural Model-Based Reinforcement Learning for Recommendation》
No 6. 《Pay Less Attention with Lightweight and Dynamic Convolutions》
No 7. 《Recurrent Neural Networks for Time Series Forecasting》
No 8. 《InstaGAN: Instance-aware Image-to-Image Translation》
No 9. 《The Matrix Calculus You Need For Deep Learning》
No 10. 《EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning》
No 11. 《Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling》
No 12. 《Visualizing Deep Similarity Networks》
No 13. 《A Comprehensive Survey on Graph Neural Networks》
No 14. 《Improving Generalization and Stability of Generative Adversarial Networks》
No 15. 《Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization》
No 16. 《Multi-class Classification without Multi-class Labels》
No 17. 《BA-Net: Dense Bundle Adjustment Networks》
No 18. 《Temporal Difference Variational Auto-Encoder》
No 19. 《Dynamic Planning Networks》
No 20. 《Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks》
No 21. 《Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms》
No 22. 《3D Convolution on RGB-D Point Clouds for Accurate Model-free Object Pose Estimation》
No 23. 《Machine learning in resting-state fMRI analysis》
No 24. 《Finger-GAN: Generating Realistic Fingerprint Images Using Connectivity Imposed GAN》
No 25. 《KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks》
No 26. 《Multiple Sclerosis Lesion Inpainting Using Non-Local Partial Convolutions》
No 27. 《Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach》
No 28. 《RegNet: Learning the Optimization of Direct Image-to-Image Pose Registration》
No 29. 《Lagging Inference Networks and Posterior Collapse in Variational Autoencoders》
No 30. 《A Theoretical Analysis of Deep Q-Learning》

No 1. 【医疗深度学习指南(综述)】
No 2. 《A Comprehensive Survey on Graph Neural Networks》
No 3. 《Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context》
No 4. 【BERT句法表示能力实验评测:各项测试均表现出色】
No 5. 《Panoptic Feature Pyramid Networks》
No 6. 【基于深度网络的心脏病专家级动态心电图心律失常检测和分类】
No 7. 《A New Perspective on Machine Learning: How to do Perfect Supervised Learning》
No 8. 《Flow Based Self-supervised Pixel Embedding for Image Segmentation》
No 9. 《On the Dimensionality of Embeddings for Sparse Features and Data》
No 10. 《Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation》
No 11. 《Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination》
No 12. 《Detecting Text in the Wild with Deep Character Embedding Network》
No 13. 《A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference》
No 14. 《Dataset Distillation》
No 15. 《What do Language Representations Really Represent?》
No 16. 《Learning Graph Embedding with Adversarial Training Methods》
No 17. 《A Survey on Multi-output Learning》
No 18. 《Attribute-Aware Attention Model for Fine-grained Representation Learning》
No 19. 《Multi-stream CNN based Video Semantic Segmentation for Automated Driving》
No 20. 《3D Point-Capsule Networks》
No 21. 《I Can See Clearly Now : Image Restoration via De-Raining》
No 22. 《Learning Independent Object Motion from Unlabelled Stereoscopic Videos》
No 23. 《Poincaré Wasserstein Autoencoder》
No 24. 《Visualizing Deep Similarity Networks》
No 25. 《Multi-class Classification without Multi-class Labels》
No 26. 《Generalization in Deep Networks: The Role of Distance from Initialization》
No 27. 《Deep Neural Network Approximation Theory》
No 28. 《On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games》
No 29. 《Explanatory Graphs for CNNs》
No 30. 《Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks》

No 1. 《Deep Learning for Anomaly Detection: A Survey》
No 2. 《Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation》
No 3. 《FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review》
No 4. 【让照片里的人物“走两步”:单张图片3D 角色动画合成】
No 5. 《Image Transformation can make Neural Networks more robust against Adversarial Examples》
No 6. 《Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit》
No 7. 《Optimization Models for Machine Learning: A Survey》
No 8. 《GILT: Generating Images from Long Text》
No 9. 《Human few-shot learning of compositional instructions》
No 10. 《Event detection in Twitter: A keyword volume approach》
No 11. 《Active Learning with TensorBoard Projector》
No 12. 《Interpretable machine learning: definitions, methods, and applications》
No 13. 《Identifying and Correcting Label Bias in Machine Learning》
No 14. 《MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks》
No 15. 《DSConv: Efficient Convolution Operator》
No 16. 《Multi-task Learning with Gradient Communication》
No 17. 《Learning-based Optimization of the Under-sampling Pattern in MRI》
No 18. 【用神经进化设计神经网络】
No 19. 《Exploiting Synchronized Lyrics And Vocal Features For Music Emotion Detection》
No 20. 《Interpretable BoW Networks for Adversarial Example Detection》
No 21. 《Understanding the (un)interpretability of natural image distributions using generative models》
No 22. 《Deep Learning for Human Affect Recognition: Insights and New Developments》
No 23. 《Manipulating and Measuring Model Interpretability》
No 24. 《Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context》
No 25. 《The Benefits of Over-parameterization at Initialization in Deep ReLU Networks》
No 26. 《Inference of Demographic Attributes based on Mobile Phone Usage Patterns and Social Network Topology》
No 27. 《Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air》
No 28. 《A Scalable Framework for Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters with Weight and Workload Balancing》
No 29. 【BERT句法表示能力实验评测:各项测试均表现出色】
No 30. 《Unsupervised Moving Object Detection via Contextual Information Separation》

No 1. 【让照片里的人物“走两步”:单张图片3D 角色动画合成】
No 2. 《Artificial Neural Networks》
No 3. 《A Survey of the Recent Architectures of Deep Convolutional Neural Networks》
No 4. 【深度卷积网络高效计算进展】
No 5. 《Attentive Neural Processes》
No 6. 【从图片到涂鸦:高品质涂鸦的自动生成(推断)】
No 7. 《Real-time Joint Object Detection and Semantic Segmentation Network for Automated Driving》
No 8. 《PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume》
No 9. 《CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation》
No 10. 《Cross-lingual Language Model Pretraining》
No 11. 《Understanding Geometry of Encoder-Decoder CNNs》
No 12. 《Task representations in neural networks trained to perform many cognitive tasks | Nature Neuroscience》
No 13. 《Bayesian Learning of Neural Network Architectures》
No 14. 《AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving》
No 15. 《Passage Re-ranking with BERT》
No 16. 《Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors》
No 17. 《Good Similar Patches for Image Denoising》
No 18. 《Improved Selective Refinement Network for Face Detection》
No 19. 《A Performance Comparison of Loss Functions for Deep Face Recognition》
No 20. 《FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network》
No 21. 《Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction》
No 22. 《A Random Walk Approach to First-Order Stochastic Convex Optimization》
No 23. 《Hierarchical Representations with Poincaré Variational Auto-Encoders》
No 24. 《Hierarchical Reinforcement Learning for Multi-agent MOBA Game》
No 25. 《Attention-aware Multi-stroke Style Transfer》
No 26. 《Consistent Optimization for Single-Shot Object Detection》
No 27. 《CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning》
No 28. 《DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features》
No 29. 《WALL-E: An Efficient Reinforcement Learning Research Framework》
No 30. 《Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the DQN Target》

No 1. 《One-Class Convolutional Neural Network》
No 2. 《The Evolved Transformer》
No 3. 《BioBERT: pre-trained biomedical language representation model for biomedical text mining》
No 4. 《Deep Learning on Small Datasets without Pre-Training using Cosine Loss》
No 5. 《A BERT Baseline for the Natural Questions》
No 6. 【综述:大脑误差反向传播理论】
No 7. 《Glyce: Glyph-vectors for Chinese Character Representations》
No 8. 《Hotels-50K: A Global Hotel Recognition Dataset》
No 9. 《Fixup Initialization: Residual Learning Without Normalization》
No 10. 《Self-Supervised Generalisation with Meta Auxiliary Learning》
No 11. 《MONet: Unsupervised Scene Decomposition and Representation》
No 12. 《Disentangling Disentanglement in Variational Auto-Encoders》
No 13. 《Design of Real-time Semantic Segmentation Decoder for Automated Driving》
No 14. 《Random Forest with Learned Representations for Semantic Segmentation》
No 15. 《In Defense of the Triplet Loss for Visual Recognition》
No 16. 《Joint shape learning and segmentation for medical images using a minimalistic deep network》
No 17. 《Theoretically Principled Trade-off between Robustness and Accuracy》
No 18. 《Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition》
No 19. 《Hierarchical Attentional Hybrid Neural Networks for Document Classification》
No 20. 《Towards a Deeper Understanding of Adversarial Losses》
No 21. 《Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System》
No 22. 《Self-Supervised Deep Image Denoising》
No 23. 《What does the free energy principle tell us about the brain?》
No 24. 《Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks》
No 25. 《Hierarchically Clustered Representation Learning》
No 26. 《Max-margin Class Imbalanced Learning with Gaussian Affinity》
No 27. 《Fast Markov Chain Monte Carlo Algorithms via Lie Groups》
No 28. 《Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge》
No 29. 《Reward Shaping via Meta-Learning》
No 30. 《Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability》

No 1. 《Visual SLAM: Why Bundle Adjust?》
No 2. 《Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher》
No 3. 《Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image Classification》
No 4. 《Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet》
No 5. 【浏览器里的胸片自动诊断工具(本地运行,保护隐私)】
No 6. 《Graph Classification with Recurrent Variational Neural Networks》
No 7. 《EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks》
No 8. 《CHIP: Channel-wise Disentangled Interpretation of Deep Convolutional Neural Networks》
No 9. 《A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases》
No 10. 《Real-time 3D Traffic Cone Detection for Autonomous Driving》
No 11. 《Scaling computational genomics to millions of individuals with GPUs》
No 12. 《A Simple Baseline for Bayesian Uncertainty in Deep Learning》
No 13. 《Natural Language Processing, Sentiment Analysis and Clinical Analytics》
No 14. 《Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level》
No 15. 《Multi-dimensional Tensor Sketch》
No 16. 《Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey》
No 17. 《Deep Reinforcement Learning from Policy-Dependent Human Feedback》
No 18. 《SiamVGG: Visual Tracking using Deeper Siamese Networks》
No 19. 《Stochastic Gradient Descent Escapes Saddle Points Efficiently》
No 20. 《Task2Vec: Task Embedding for Meta-Learning》
No 21. 《BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model》
No 22. 《Conditional BERT Contextual Augmentation》
No 23. 《The role of a layer in deep neural networks: a Gaussian Process perspective》
No 24. 《Advances on CNN-based super-resolution of Sentinel-2 images》
No 25. 《Generalized Sliced Wasserstein Distances》
No 26. 《DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion》
No 27. 《Unsupervised Data Uncertainty Learning in Visual Retrieval Systems》
No 28. 《Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation》
No 29. 《Negative eigenvalues of the Hessian in deep neural networks》
No 30. 《Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks》

No 1. 【基于GAN的人脸照片涂鸦编辑,可添加/更改耳环,眼镜,发型,酒窝等】
No 2. 《Fast-SCNN: Fast Semantic Segmentation Network》
No 3. 《Fake News Detection on Social Media using Geometric Deep Learning》
No 4. 《Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent》
No 5. 《Augmentation for small object detection》
No 6. 《Contextual Word Representations: A Contextual Introduction》
No 7. 《DeeperLab: Single-Shot Image Parser》
No 8. 《On the Impact of the Activation Function on Deep Neural Networks Training》
No 9. 《AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling》
No 10. 《Deep Learning for Image Super-resolution: A Survey》
No 11. 《Simplifying Graph Convolutional Networks》
No 12. 《ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing》
No 13. 【深度流体:GAN参数化流体模拟】
No 14. 《Do ImageNet Classifiers Generalize to ImageNet?》
No 15. 《Context-Aware Self-Attention Networks》
No 16. 《A Simple Method for Commonsense Reasoning》
No 17. 《A Generalized Framework for Population Based Training》
No 18. 《Heartbeat Anomaly Detection using Adversarial Oversampling》
No 19. 《BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding》
No 20. 《Probabilistic Neural Architecture Search》
No 21. 《On Evaluating Adversarial Robustness》
No 22. 《Seven Myths in Machine Learning Research》
No 23. 《Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations》
No 24. 《Learning interpretable continuous-time models of latent stochastic dynamical systems》
No 25. 《Heterogeneous Edge Embeddings for Friend Recommendation》
No 26. 《Discovery of Natural Language Concepts in Individual Units of CNNs》
No 27. 《World Discovery Models》
No 28. 《An attention based deep learning model of clinical events in the intensive care unit》
No 29. 《A Theory of Selective Prediction》
No 30. 《Fast Efficient Hyperparameter Tuning for Policy Gradients》

No 1. 《Parsing Gigabytes of JSON per Second》
No 2. 【Bio-LSTM人体运动(姿态/步法)预测】
No 3. 《Deep High-Resolution Representation Learning for Human Pose Estimation》
No 4. 《GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction》
No 5. 《Spreading vectors for similarity search》
No 6. 【曲率正则化与鲁棒性的双向增强:对抗训练可有效提高分类器鲁棒性,其几何表征非常简单,基于此反向设计有效的正则化提高对抗性】
No 7. 《GeoGAN: A Conditional GAN with Reconstruction and Style Loss to Generate Standard Layer of Maps from Satellite Images》
No 8. 【基于GAN的人脸照片涂鸦编辑,可添加/更改耳环,眼镜,发型,酒窝等】
No 9. 《PIXOR: Real-time 3D Object Detection from Point Clouds》
No 10. 《Bayesian Anomaly Detection and Classification》
No 11. 《Adaptive Gradient Methods with Dynamic Bound of Learning Rate(AdaBound)》
No 12. 《Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling》
No 13. 《A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting》
No 14. 《BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding》
No 15. 《Online Meta-Learning》
No 16. 《A Mean Field Theory of Batch Normalization》
No 17. 《Attention is not Explanation》
No 18. 《Ising-Dropout: A Regularization Method for Training and Compression of Deep Neural Networks》
No 19. 《The State of Sparsity in Deep Neural Networks》
No 20. 《Financial series prediction using Attention LSTM》
No 21. 《Online Multi-Object Tracking with Instance-Aware Tracker and Dynamic Model Refreshment》
No 22. 《Robust Graph Embedding with Noisy Link Weights》
No 23. 《Scalable Hyperbolic Recommender Systems》
No 24. 【生物神经网络与人工神经网络分析:协同的挑战和机遇?】
No 25. 《Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection》
No 26. 《GANSynth: Adversarial Neural Audio Synthesis》
No 27. 《The State of the Art in Multilayer Network Visualization》
No 28. 《LocalNorm: Robust Image Classification through Dynamically Regularized Normalization》
No 29. 《Transfusion: Understanding Transfer Learning with Applications to Medical Imaging》
No 30. 《GSLAM: A General SLAM Framework and Benchmark》

No 1. 《Attention is not Explanation》
No 2. 《Financial series prediction using Attention LSTM》
No 3. 《Insights into LSTM Fully Convolutional Networks for Time Series Classification》
No 4. 《High-Fidelity Image Generation With Fewer Labels》
No 5. 《Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning》
No 6. 《Detecting Overfitting via Adversarial Examples》
No 7. 《A Joint Deep Learning Approach for Automated Liver and Tumor Segmentation》
No 8. 《Data augmentation using learned transforms for one-shot medical image segmentation》
No 9. 《VideoFlow: A Flow-Based Generative Model for Video》
No 10. 《Degenerate Feedback Loops in Recommender Systems》
No 11. 《Evaluating Feature Importance Estimates》
No 12. 《Video Face Recognition: Component-wise Feature Aggregation Network (C-FAN)》
No 13. 《Fast Graph Representation Learning with PyTorch Geometric》
No 14. 《Structure Tree-LSTM: Structure-aware Attentional Document Encoders》
No 15. 《Learning a smooth kernel regularizer for convolutional neural networks》
No 16. 《Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach》
No 17. 《Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data》
No 18. 《DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs》
No 19. 《Adversarial Attacks on Time Series》
No 20. 《A comparative evaluation of novelty detection algorithms for discrete sequences》
No 21. 《Evolutionary Neural AutoML for Deep Learning》
No 22. 《Efficient Contextual Representation Learning Without Softmax Layer》
No 23. 《Large-Scale Object Mining for Object Discovery from Unlabeled Video》
No 24. 《Entity Recognition at First Sight: Improving NER with Eye Movement Information》
No 25. 《A Mean Field Theory of Batch Normalization》
No 26. 《Nonlinear Markov Random Fields Learned via Backpropagation》
No 27. 《Learning to Plan via Neural Exploration-Exploitation Trees》
No 28. 《Using Natural Language for Reward Shaping in Reinforcement Learning》
No 29. 《ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape》
No 30. 《Automated Model Selection with Bayesian Quadrature》

No 1. 《A Mean Field Theory of Batch Normalization》
No 2. 《Gradient Descent based Optimization Algorithms for Deep Learning Models Training》
No 3. 《Efficient Parameter-free Clustering Using First Neighbor Relations》
No 4. 《Deep CNN-based Multi-task Learning for Open-Set Recognition》
No 5. 《Theory III: Dynamics and Generalization in Deep Networks》
No 6. 《Financial Applications of Gaussian Processes and Bayesian Optimization》
No 7. 《Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems》
No 8. 《GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier》
No 9. 《Hierarchical Autoregressive Image Models with Auxiliary Decoders》
No 10. 《The Evolved Transformer》
No 11. 《Ranked List Loss for Deep Metric Learning》
No 12. 《Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation》
No 13. 《When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies》
No 14. 《Learning deep neural networks in blind deblurring framework》
No 15. 《Neural Language Modeling with Visual Features》
No 16. 《Graph-RISE: Graph-Regularized Image Semantic Embedding》
No 17. 《Why Learning of Large-Scale Neural Networks Behaves Like Convex Optimization》
No 18. 《Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning》
No 19. 《A Survey on Graph Processing Accelerators: Challenges and Opportunities》
No 20. 《3DN: 3D Deformation Network》
No 21. 《The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamics》
No 22. 《A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission》
No 23. 《Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation》
No 24. 《Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss》
No 25. 《Deep Embeddings for Rare Audio Event Detection With Imbalanced Data》
No 26. 《GCNv2: Efficient Correspondence Prediction for Real-Time SLAM》
No 27. 《RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion》
No 28. 《Context-Aware Learning for Neural Machine Translation》
No 29. 《PanopticFusion: Online Volumetric Semantic Mapping at the Level of Stuff and Things》
No 30. 《RVOS: End-to-End Recurrent Network for Video Object Segmentation》

No 1. 【将涂鸦生成逼真照片:空间自适应归一化语义图像合成】
No 2. 《A Three-Player GAN: Generating Hard Samples To Improve Classification Networks》
No 3. 《Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening》
No 4. 《Semantic Image Synthesis with Spatially-Adaptive Normalization》
No 5. 《To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks》
No 6. 《Unsupervised Network Embedding for Graph Visualization, Clustering and Classification》
No 7. 《Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases》
No 8. 【医疗机器学习对抗攻击】
No 9. 《IndyLSTMs: Independently Recurrent LSTMs》
No 10. 《Learning to Reconstruct People in Clothing from a Single RGB Camera》
No 11. 《Stiffness: A New Perspective on Generalization in Neural Networks》
No 12. 《Elements and Principles of Data Analysis》
No 13. 《Low-rank Kernel Learning for Graph-based Clustering》
No 14. 《Generative Graph Convolutional Network for Growing Graphs》
No 15. 《SR-LSTM: State Refinement for LSTM towards Pedestrian Trajectory Prediction》
No 16. 《A Graph-structured Dataset for Wikipedia Research》
No 17. 《Improving Neural Architecture Search Image Classifiers via Ensemble Learning》
No 18. 【能量模型隐式生成和泛化方法】
No 19. 《Diagnosing and Enhancing VAE Models》
No 20. 《PifPaf: Composite Fields for Human Pose Estimation》
No 21. 《Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom Up》
No 22. 《Reinforcement Learning with Dynamic Boltzmann Softmax Updates》
No 23. 《Dying ReLU and Initialization: Theory and Numerical Examples》
No 24. 《Multimodal Deep Learning for Finance: Integrating and Forecasting International Stock Markets》
No 25. 《Exact Gaussian Processes on a Million Data Points》
No 26. 《Interpretable Deep Learning in Drug Discovery》
No 27. 《Markov-chain-inspired search for MH370》
No 28. 《Extrapolating paths with graph neural networks》
No 29. 《Data-driven Neural Architecture Learning For Financial Time-series Forecasting》
No 30. 《Functional Variational Bayesian Neural Networks》

No 1. 《A Deep Look into Neural Ranking Models for Information Retrieval》
No 2. 【医疗机器学习对抗攻击】
No 3. 【综述:机器学习与物理学】
No 4. 《Linguistic Knowledge and Transferability of Contextual Representations》
No 5. 《Node Embedding over Temporal Graphs》
No 6. 《Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks》
No 7. 《Im2Pencil: Controllable Pencil Illustration from Photographs》
No 8. 《Weight Standardization》
No 9. 《Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence》
No 10. 《A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networks》
No 11. 《PI-REC: Progressive Image Reconstruction Network With Edge and Color Domain》
No 12. 《Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning》
No 13. 《nuScenes: A multimodal dataset for autonomous driving》
No 14. 《Interpretable Reinforcement Learning via Differentiable Decision Trees》
No 15. 《LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving》
No 16. 《A RAD approach to deep mixture models》
No 17. 《Implicit Generation and Generalization in Energy-Based Models》
No 18. 《Interactive segmentation of medical images through fully convolutional neural networks》
No 19. 《Network reconstruction and community detection from dynamics》
No 20. 《A Comparative Study of Different Approaches for Tracking Communities in Evolving Social Networks》
No 21. 《Recent advances in conversational NLP : Towards the standardization of Chatbot building》
No 22. 《Low Resource Text Classification with ULMFit and Backtranslation》
No 23. 《Robust Image Segmentation Quality Assessment without Ground Truth》
No 24. 《Monte Carlo Neural Fictitious Self-Play: Achieve Approximate Nash equilibrium of Imperfect-Information Games》
No 25. 《Interpreting Neural Networks Using Flip Points》
No 26. 《Eigenvalue and Generalized Eigenvalue Problems: Tutorial》
No 27. 《Learning to Paint with Model-based Deep Reinforcement Learning》
No 28. 《Corners for Layout: End-to-End Layout Recovery from 360 Images》
No 29. 《How Can We Be So Dense? The Benefits of Using Highly Sparse Representations》
No 30. 《Multi-Object Representation Learning with Iterative Variational Inference》

No 1. 《Reducing BERT Pre-Training Time from 3 Days to 76 Minutes》
No 2. 《PyTorch-BigGraph: A Large-scale Graph Embedding System》
No 3. 《FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation》
No 4. 【综述:机器学习与物理学】
No 5. 《Fast video object segmentation with Spatio-Temporal GANs》
No 6. 《Why ResNet Works? Residuals Generalize》
No 7. 《A Survey on Graph Kernels》
No 8. 《Feature Fusion Encoder Decoder Network For Automatic Liver Lesion Segmentation》
No 9. 《Yet Another Accelerated SGD: ResNet-50 Training on ImageNet in 74.7 seconds》
No 10. 《Analysing Mathematical Reasoning Abilities of Neural Models》
No 11. 《Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration》
No 12. 《ThunderNet: Towards Real-time Generic Object Detection》
No 13. 《PI-REC: Progressive Image Reconstruction Network With Edge and Color Domain》
No 14. 《A Dataset for Semantic Segmentation of Point Cloud Sequences》
No 15. 《Wasserstein Dependency Measure for Representation Learning》
No 16. 《Image Generation from Small Datasets via Batch Statistics Adaptation》
No 17. 《Residual Pyramid Learning for Single-Shot Semantic Segmentation》
No 18. 《Pyramid Mask Text Detector》
No 19. 《Self-Supervised Learning via Conditional Motion Propagation》
No 20. 《MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning》
No 21. 《Exploring Randomly Wired Neural Networks for Image Recognition》
No 22. 《Multi-Domain Adversarial Learning》
No 23. 《Augmented Neural ODEs》
No 24. 《Sparse2Dense: From direct sparse odometry to dense 3D reconstruction》
No 25. 《Meta-Learning surrogate models for sequential decision making》
No 26. 《Photorealistic Style Transfer via Wavelet Transforms》
No 27. 《Distilling Task-Specific Knowledge from BERT into Simple Neural Networks》
No 28. 《Learning to Paint with Model-based Deep Reinforcement Learning》
No 29. 《Eigenvalue and Generalized Eigenvalue Problems: Tutorial》
No 30. 《Machine Learning for Data-Driven Movement Generation: a Review of the State of the Art》

No 1. 【可扩展肌肉驱动人体模拟与控制(SIGGRAPH 2019):深度强化学习运动模拟,基于全身肌肉骨骼模型,包含346块肌肉,可进行术后步态预测模拟】
No 2. 【Curve-GCN交互式图像标注,性能优于Polygon-RNN++,速度提高10倍】
No 3. 《An Attentive Survey of Attention Models》
No 4. 《Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving》
No 5. 《Text Generation from Knowledge Graphs with Graph Transformers》
No 6. 《Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction》
No 7. 《Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection》
No 8. 《VideoBERT: A Joint Model for Video and Language Representation Learning》
No 9. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》
No 10. 《Sogou Machine Reading Comprehension Toolkit》
No 11. 《Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections》
No 12. 《A Selective Overview of Deep Learning》
No 13. 《Learning Discrete Structures for Graph Neural Networks》
No 14. 《High-Resolution Representations for Labeling Pixels and Regions》
No 15. 《A Robust Learning Approach to Domain Adaptive Object Detection》
No 16. 《Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras》
No 17. 《A New GAN-based End-to-End TTS Training Algorithm》
No 18. 《Attention is not Explanation》
No 19. 《Probing Biomedical Embeddings from Language Models》
No 20. 《ASAP: Architecture Search, Anneal and Prune》
No 21. 《Reinforcement Learning with Attention that Works: A Self-Supervised Approach》
No 22. 《Spatially Controllable Image Synthesis with Internal Representation Collaging》
No 23. 《MVX-Net: Multimodal VoxelNet for 3D Object Detection》
No 24. 《Training a Neural Speech Waveform Model using Spectral Losses of Short-Time Fourier Transform and Continuous Wavelet Transform》
No 25. 《Data-Free Learning of Student Networks》
No 26. 【NAACL 2019 Best Paper Awards】
No 27. 《Bayesian Mixed Effect Sparse Tensor Response Regression Model with Joint Estimation of Activation and Connectivity》
No 28. 《Towards Real-Time Automatic Portrait Matting on Mobile Devices》
No 29. 【文本动画生成:迪士尼用脚本直接生成故事板动画】
No 30. 《Community Detection in Social Network using Temporal Data》

No 1. 《Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution》
No 2. 《NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection》
No 3. 《Text Classification Algorithms: A Survey》
No 4. 《A Selective Overview of Deep Learning》
No 5. 【机器学习在药物研发中的应用】
No 6. 【文本动画生成:迪士尼用脚本直接生成故事板动画】
No 7. 《DocBERT: BERT for Document Classification》
No 8. 【自适应深度重用(Adaptive Deep Reuse):将卷积网络训练时间减少69%】
No 9. 《Objects as Points》
No 10. 《A Discussion on Solving Partial Differential Equations using Neural Networks》
No 11. 【在线/离线测试结合改进新闻信息流排序】
No 12. 《Singing voice synthesis based on convolutional neural networks》
No 13. 《Attention Branch Network: Learning of Attention Mechanism for Visual Explanation》
No 14. 《Pixel-Adaptive Convolutional Neural Networks》
No 15. 【(综述)深度学习:基因组学的新计算建模技术】
No 16. 《Metrics for Graph Comparison: A Practitioner's Guide》
No 17. 《Generative Adversarial Networks for text using word2vec intermediaries》
No 18. 《wav2vec: Unsupervised Pre-training for Speech Recognition》
No 19. 《BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis》
No 20. 《Deep Neural Network Ensembles》
No 21. 《3D Dense Face Alignment via Graph Convolution Networks》
No 22. 《Learning Single Camera Depth Estimation using Dual-Pixels》
No 23. 《Contextualized Word Representations for Document Re-Ranking》
No 24. 《DAGCN: Dual Attention Graph Convolutional Networks》
No 25. 《Stock Forecasting using M-Band Wavelet-Based SVR and RNN-LSTMs Models》
No 26. 《FTGAN: A Fully-trained Generative Adversarial Networks for Text to Face Generation》
No 27. 《Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization》
No 28. 《Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres》
No 29. 《Enhancing Time Series Momentum Strategies Using Deep Neural Networks》
No 30. 《Recurrent Event Network for Reasoning over Temporal Knowledge Graphs》

No 1. 【今日焦点:用对抗补丁骗过AI监控摄像头】
No 2. 《4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks》
No 3. 《Understanding Neural Networks via Feature Visualization: A survey》
No 4. 《CenterNet: Keypoint Triplets for Object Detection》
No 5. 《TextCaps : Handwritten Character Recognition with Very Small Datasets》
No 6. 《Language Models with Transformers》
No 7. 【稀疏Transformer生成式建模:深度网络(文本、图像、声音)序列内容预测,改进的注意机制使其从序列中提取模式比以前的时长长30倍】
No 8. 《Relational Graph Attention Networks》
No 9. 《Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering》
No 10. 《Attention Augmented Convolutional Networks》
No 11. 《An Empirical Study of Spatial Attention Mechanisms in Deep Networks》
No 12. 《Optimal initialization of K-means using Particle Swarm Optimization》
No 13. 《YUVMultiNet: Real-time YUV multi-task CNN for autonomous driving》
No 14. 《Stock Forecasting using M-Band Wavelet-Based SVR and RNN-LSTMs Models》
No 15. 《PointConv: Deep Convolutional Networks on 3D Point Clouds》
No 16. 《Understanding the Behaviors of BERT in Ranking》
No 17. 《Explaining Deep Classification of Time-Series Data with Learned Prototypes》
No 18. 《MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning》
No 19. 《Ranking-Based Autoencoder for Extreme Multi-label Classification》
No 20. 《Predicting human decisions with behavioral theories and machine learning》
No 21. 《What is the effect of Importance Weighting in Deep Learning?》
No 22. 《Low-Memory Neural Network Training: A Technical Report》
No 23. 《Dynamic Evaluation of Transformer Language Models》
No 24. 《Learning Digital Camera Pipeline for Extreme Low-Light Imaging》
No 25. 《Unsupervised Person Image Generation with Semantic Parsing Transformation》
No 26. 《End-to-End Robotic Reinforcement Learning without Reward Engineering》
No 27. 《Fashion++: Minimal Edits for Outfit Improvement》
No 28. 《Introduction to Multi-Armed Bandits》
No 29. 《Quaternion Knowledge Graph Embedding》
No 30. 《Tex2Shape: Detailed Full Human Body Geometry from a Single Image》

No 1. 《Neural Logic Machines》
No 2. 《Graph Matching Networks for Learning the Similarity of Graph Structured Objects》
No 3. 《Survey on Automated Machine Learning》
No 4. 《Low-Memory Neural Network Training: A Technical Report》
No 5. 《From GAN to WGAN》
No 6. 《Graph Kernels: A Survey》
No 7. 【实数,数据科学与混沌:单参数拟合任意数据集】
No 8. 《Unsupervised Data Augmentation》
No 9. 《Context-Aware Zero-Shot Recognition》
No 10. 《On the Mathematical Understanding of ResNet with Feynman Path Integral》
No 11. 《Deep Representation Learning for Social Network Analysis》
No 12. 《RepPoints: Point Set Representation for Object Detection》
No 13. 《Learning Discriminative Features Via Weights-biased Softmax Loss》
No 14. 【波动物理学模拟RNN:无需模数转换的信号原生域RNN】
No 15. 《Deep Metric Learning Beyond Binary Supervision》
No 16. 【快速鲁棒的动物姿态估计】
No 17. 《STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing》
No 18. 【“走四方”的敏捷两足行走机器人:迭代强化学习动态运动技能设计】
No 19. 【Vid2Game:从真实场景视频提取可控制角色】
No 20. 《High-Performance Support Vector Machines and Its Applications》
No 21. 《Fast AutoAugment》
No 22. 《Graph Element Networks: adaptive, structured computation and memory》
No 23. 《Challenges and Prospects in Vision and Language Research》
No 24. 《Inpatient2Vec: Medical Representation Learning for Inpatients》
No 25. 《Decision Forest: A Nonparametric Approach to Modeling Irrational Choice》
No 26. 《Unsupervised deep learning for Bayesian brain MRI segmentation》
No 27. 《Meta-Sim: Learning to Generate Synthetic Datasets》
No 28. 《ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning》
No 29. 《Unsupervised label noise modeling and loss correction》
No 30. 《Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks》

No 1. 【比MobileNetV2快2倍更准确的MobileNetV3】
No 2. 《Survey of Dropout Methods for Deep Neural Networks》
No 3. 《Low-Memory Neural Network Training: A Technical Report》
No 4. 《A Survey on Neural Architecture Search》
No 5. 《Graph Matching Networks for Learning the Similarity of Graph Structured Objects》
No 6. 《Unified Language Model Pre-training for Natural Language Understanding and Generation》
No 7. 【深度学习蛋白质序列标注与功能预测】
No 8. 《Adversarial Examples Are Not Bugs, They Are Features》
No 9. 【Few-Shot无监督图到图变换:从少量样本挖掘新事物特质】
No 10. 《WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving》
No 11. 《Billion-scale semi-supervised learning for image classification》
No 12. 《The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks》
No 13. 《Self-supervised Learning for Video Correspondence Flow》
No 14. 《Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks》
No 15. 《HAR-Net: Joint Learning of Hybrid Attention for Single-stage Object Detection》
No 16. 《Deep Learning for Audio Signal Processing》
No 17. 《Bayesian Optimization using Deep Gaussian Processes》
No 18. 《Convolutional Mesh Regression for Single-Image Human Shape Reconstruction》
No 19. 《FAQ Retrieval using Query-Question Similarity and BERT-Based Query-Answer Relevance》
No 20. 《Meta-learning of Sequential Strategies》
No 21. 《GAN Augmented Text Anomaly Detection with Sequences of Deep Statistics》
No 22. 《ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning》
No 23. 《Self-Supervised Convolutional Subspace Clustering Network》
No 24. 《Full-Jacobian Representation of Neural Networks》
No 25. 《Estimating Kullback-Leibler Divergence Using Kernel Machines》
No 26. 《Reducing Anomaly Detection in Images to Detection in Noise》
No 27. 《26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone》
No 28. 《Challenges of Real-World Reinforcement Learning》
No 29. 《Controllable Artistic Text Style Transfer via Shape-Matching GAN》
No 30. 《3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams》

No 1. 《Object Detection in 20 Years: A Survey》
No 2. 【视频三维人体动态学习】
No 3. 《Learning Embeddings into Entropic Wasserstein Spaces》
No 4. 《Bayesian Optimization using Deep Gaussian Processes》
No 5. 《Embedding Human Knowledge in Deep Neural Network via Attention Map》
No 6. 《D2-Net: A Trainable CNN for Joint Detection and Description of Local Features》
No 7. 《Graph U-Nets》
No 8. 《Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks》
No 9. 《Graph Convolutional Gaussian Processes》
No 10. 《Targeted Sentiment Analysis: A Data-Driven Categorization》
No 11. 《S4L: Self-Supervised Semi-Supervised Learning》
No 12. 《Learning Loss for Active Learning》
No 13. 《Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting》
No 14. 《MASS: Masked Sequence to Sequence Pre-training for Language Generation》
No 15. 【人体姿态可学习三角测量】
No 16. 《Zero-Shot Voice Style Transfer with Only Autoencoder Loss》
No 17. 《Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs》
No 18. 《Meta-Learning with Differentiable Convex Optimization》
No 19. 《MeshCNN: A Network with an Edge》
No 20. 《Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping》
No 21. 《RadiX-Net: Structured Sparse Matrices for Deep Neural Networks》
No 22. 《Interdisciplinary Relationships Between Biological and Physical Sciences》
No 23. 《Interactive Image Generation Using Scene Graphs》
No 24. 《Multi-Person Pose Estimation with Enhanced Channel-wise and Spatial Information》
No 25. 《Evaluation of Machine Learning Classifiers for Zero-Day Intrusion Detection -- An Analysis on CIC-AWS-2018 dataset》
No 26. 《Structural Equation Modeling using Computation Graphs》
No 27. 《Machine Learning at Microsoft with ML .NET》
No 28. 《AutoAssist: A Framework to Accelerate Training of Deep Neural Networks》
No 29. 《Learning Causality: Synthesis of Large-Scale Causal Networks from High-Dimensional Time Series Data》
No 30. 《Learning to Interpret Satellite Images in Global Scale Using Wikipedia》

No 1. 【用目标人物少量图片(甚至一张图片)来制作头部动画——关键点/自适应实例规范化/GAN,无需3D人脸建模】
No 2. 《Learning What and Where to Transfer》
No 3. 《Which Tasks Should Be Learned Together in Multi-task Learning?》
No 4. 《Behavior Sequence Transformer for E-commerce Recommendation in Alibaba》
No 5. 《From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec》
No 6. 《Deep Compressed Sensing》
No 7. 《How do neural networks see depth in single images?》
No 8. 《Joint Learning of Neural Networks via Iterative Reweighted Least Squares》
No 9. 《LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning》
No 10. 《Simple Black-box Adversarial Attacks》
No 11. 《Meta reinforcement learning as task inference》
No 12. 《Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach》
No 13. 《PEPSI++: Fast and Lightweight Network for Image Inpainting》
No 14. 《Language-Conditioned Graph Networks for Relational Reasoning》
No 15. 《Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care》
No 16. 《The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions》
No 17. 《LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations》
No 18. 《Explainable AI for Trees: From Local Explanations to Global Understanding》
No 19. 《Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering》
No 20. 《FastSpeech: Fast, Robust and Controllable Text to Speech》
No 21. 《Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative》
No 22. 《On Variational Bounds of Mutual Information》
No 23. 《Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search》
No 24. 《Learnable Triangulation of Human Pose》
No 25. 《Time-varying Autoregression with Low Rank Tensors》
No 26. 《Approximate Bayesian computation with the Wasserstein distance》
No 27. 《Data-Efficient Image Recognition with Contrastive Predictive Coding》
No 28. 《The Mobility Network of Scientists: Analyzing Temporal Correlations in Scientific Careers》
No 29. 《Parallel Neural Text-to-Speech》
No 30. 《Interpretable Neural Predictions with Differentiable Binary Variables》

No 1. 《EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks》
No 2. 《Pre-training Graph Neural Networks》
No 3. 《Speech2Face: Learning the Face Behind a Voice》
No 4. 《Light-Weight RetinaNet for Object Detection》
No 5. 【无需3D显式形状建模的神经网络3D角色贴图】
No 6. 《The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial》
No 7. 《Revisiting Graph Neural Networks: All We Have is Low-Pass Filters》
No 8. 《FAN: Focused Attention Networks》
No 9. 《Stabilizing GANs with Octave Convolutions》
No 10. 《FaceSwapNet: Landmark Guided Many-to-Many Face Reenactment》
No 11. 《Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned》
No 12. 《Graph Learning Network: A Structure Learning Algorithm》
No 13. 《Training language GANs from Scratch》
No 14. 《Disentangling Style and Content in Anime Illustrations》
No 15. 《Bayesian Anomaly Detection Using Extreme Value Theory》
No 16. 《Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks》
No 17. 《What is the Entropy of a Social Organization?》
No 18. 《6-DOF GraspNet: Variational Grasp Generation for Object Manipulation》
No 19. 《Levenshtein Transformer》
No 20. 《Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces》
No 21. 《Adversarial Policies: Attacking Deep Reinforcement Learning》
No 22. 《Adaptive Deep Kernel Learning》
No 23. 《Discovering Hidden Structure in High Dimensional Human Behavioral Data via Tensor Factorization》
No 24. 《SMART: Semantic Malware Attribute Relevance Tagging》
No 25. 《N-BEATS: Neural basis expansion analysis for interpretable time series forecasting》
No 26. 《Capsule Routing via Variational Bayes》
No 27. 《Object Discovery with a Copy-Pasting GAN》
No 28. 《Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks》
No 29. 《Are Sixteen Heads Really Better than One?》
No 30. 《Video-to-Video Translation for Visual Speech Synthesis》

No 1. 《The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial》
No 2. 《Graph Learning Network: A Structure Learning Algorithm》
No 3. 《A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends》
No 4. 《Approximate Inference Turns Deep Networks into Gaussian Processes》
No 5. 《RF-Net: An End-to-End Image Matching Network based on Receptive Field》
No 6. 《Toward Self-Supervised Object Detection in Unlabeled Videos》
No 7. 《Generative Imaging and Image Processing via Generative Encoder》
No 8. 《EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks》
No 9. 《How to Initialize your Network? Robust Initialization for WeightNorm & ResNets》
No 10. 《Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization》
No 11. 《High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks》
No 12. 《A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities》
No 13. 《Path-Augmented Graph Transformer Network》
No 14. 《What Can Neural Networks Reason About?》
No 15. 《Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels》
No 16. 《Luck Matters: Understanding Training Dynamics of Deep ReLU Networks》
No 17. 《Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks》
No 18. 《Ensemble MCMC: Accelerating Pseudo-Marginal MCMC for State Space Models using the Ensemble Kalman Filter》
No 19. 《Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae》
No 20. 《Generating Diverse High-Fidelity Images with VQ-VAE-2》
No 21. 《Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training》
No 22. 《Graph Representations for Higher-Order Logic and Theorem Proving》
No 23. 《Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology》
No 24. 《Unsupervised Paraphrasing without Translation》
No 25. 《Wasserstein Style Transfer》
No 26. 《The Strength of Structural Diversity in Online Social Networks》
No 27. 《Equivalent and Approximate Transformations of Deep Neural Networks》
No 28. 《Counting Causal Paths in Big Times Series Data on Networks》
No 29. 《Copy this Sentence》
No 30. 《Using Text Embeddings for Causal Inference》

No 1. 【深度学习电影接吻镜头检测器,2.3TB数据集,已标注100部电影包含263个接吻片段和363个非接吻片段 😗】
No 2. 《Attention Is (not) All You Need for Commonsense Reasoning》
No 3. 《Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations》
No 4. 《Is Attention Interpretable?》
No 5. 《What Does BERT Look At? An Analysis of BERT's Attention》
No 6. 【听“音”知“形”:根据语音预测(个人风格)手势,大型特定人手势视频数据集(10人/128小时)】
No 7. 《Generative Adversarial Networks: A Survey and Taxonomy》
No 8. 《Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning》
No 9. 《Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference》
No 10. 《Rates of Convergence for Sparse Variational Gaussian Process Regression》
No 11. 《Understanding Generalization through Visualizations》
No 12. 《2nd Place and 2nd Place Solution to Kaggle Landmark Recognition andRetrieval Competition 2019》
No 13. 《DiCENet: Dimension-wise Convolutions for Efficient Networks》
No 14. 《WikiDataSets : Standardized sub-graphs from WikiData》
No 15. 《Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift》
No 16. 《Automated Machine Learning: State-of-The-Art and Open Challenges》
No 17. 《Efficient Forward Architecture Search》
No 18. 《Selfie: Self-supervised Pretraining for Image Embedding》
No 19. 《How to make a pizza: Learning a compositional layer-based GAN model》
No 20. 《Deep learning for image segmentation-a short survey》
No 21. 《Particle Filter Recurrent Neural Networks》
No 22. 《Meta-Learning via Learned Loss》
No 23. 《Shapes and Context: In-the-Wild Image Synthesis & Manipulation》
No 24. 《Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network》
No 25. 《When to use parametric models in reinforcement learning?》
No 26. 《AutoGrow: Automatic Layer Growing in Deep Convolutional Networks》
No 27. 《Causal Discovery with Reinforcement Learning》
No 28. 《A Closer Look at the Optimization Landscapes of Generative Adversarial Networks》
No 29. 《Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View》
No 30. 《Learning Sparse Networks Using Targeted Dropout》

No 1. 《XLNet: Generalized Autoregressive Pretraining for Language Understanding》
No 2. 《A Survey on Neural Network Language Models》
No 3. 《Stacked Capsule Autoencoders》
No 4. 《Pre-Training with Whole Word Masking for Chinese BERT》
No 5. 《Position-aware Graph Neural Networks》
No 6. 《Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift》
No 7. 《Meta-Learning via Learned Loss》
No 8. 《PyRobot: An Open-source Robotics Framework for Research and Benchmarking》
No 9. 《A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation》
No 10. 《A Closed-Form Learned Pooling for Deep Classification Networks》
No 11. 《Matching the Blanks: Distributional Similarity for Relation Learning》
No 12. 《A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation》
No 13. 《Stand-Alone Self-Attention in Vision Models》
No 14. 《There is no general AI: Why Turing machines cannot pass the Turing test》
No 15. 《Statistical Inference for Generative Models with Maximum Mean Discrepancy》
No 16. 《Adaptive Nonparametric Variational Autoencoder》
No 17. 《PHiSeg: Capturing Uncertainty in Medical Image Segmentation》
No 18. 《Deep learning for cellular image analysis》
No 19. 【LSTM的大批量(Large-Batch)训练】
No 20. 《Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards》
No 21. 《NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language》
No 22. 《Reweighted Expectation Maximization》
No 23. 《Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification》
No 24. 《Budget-aware Semi-Supervised Semantic and Instance Segmentation》
No 25. 《Visual Relationships as Functions: Enabling Few-Shot Scene Graph Prediction》
No 26. 《Unsupervised Neural Single-Document Summarization of Reviews via Learning Latent Discourse Structure and its Ranking》
No 27. 《Self-Attentional Models for Lattice Inputs》
No 28. 《R2D2: Reliable and Repeatable Detectors and Descriptors for Joint Sparse Keypoint Detection and Local Feature Extraction》
No 29. 《GLTR: Statistical Detection and Visualization of Generated Text》
No 30. 《Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts》

No 1. 【有效降维的十个窍门】
No 2. 【单目3D人体姿态检测】
No 3. 《Learning Data Augmentation Strategies for Object Detection》
No 4. 《A Survey on GANs for Anomaly Detection》
No 5. 《Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss》
No 6. 《Grid R-CNN Plus: Faster and Better》
No 7. 《Semi-Supervised Learning with Self-Supervised Networks》
No 8. 《GAN-Knowledge Distillation for one-stage Object Detection》
No 9. 《Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era》
No 10. 《Monte Carlo Gradient Estimation in Machine Learning》
No 11. 《Reinforcement Learning with Convex Constraints》
No 12. 《A Theoretical Connection Between Statistical Physics and Reinforcement Learning》
No 13. 《Fisher and Kernel Fisher Discriminant Analysis: Tutorial》
No 14. 《Topology-Preserving Deep Image Segmentation》
No 15. 《Continual and Multi-Task Architecture Search》
No 16. 《Simplex2Vec embeddings for community detection in simplicial complexes》
No 17. 《Attention-based Conditioning Methods for External Knowledge Integration》
No 18. 《Hierarchical Representation in Neural Language Models: Suppression and Recovery of Expectations》
No 19. 《Inference for multiple heterogeneous networks with a common invariant subspace》
No 20. 《Efficient Project Gradient Descent for Ensemble Adversarial Attack》
No 21. 《Confidence Calibration for Convolutional Neural Networks Using Structured Dropout》
No 22. 《Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition》
No 23. 《DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints》
No 24. 《When to Trust Your Model: Model-Based Policy Optimization》
No 25. 《GANalyze: Toward Visual Definitions of Cognitive Image Properties》
No 26. 《Towards Inverse Reinforcement Learning for Limit Order Book Dynamics》
No 27. 《Benign Overfitting in Linear Regression》
No 28. 《Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks》
No 29. 《End-to-End 3D-PointCloud Semantic Segmentation for Autonomous Driving》
No 30. 《Spatial 3D Matérn priors for fast whole-brain fMRI analysis》

No 1. 《Modern Deep Reinforcement Learning Algorithms》
No 2. 《A Survey on GANs for Anomaly Detection》
No 3. 《Human vs Machine Attention in Neural Networks: A Comparative Study》
No 4. 《A Fourier Perspective on Model Robustness in Computer Vision》
No 5. 《Selection Via Proxy: Efficient Data Selection For Deep Learning》
No 6. 《Machine Learning Testing: Survey, Landscapes and Horizons》
No 7. 《On-Device Neural Net Inference with Mobile GPUs》
No 8. 《Causal models on probability spaces》
No 9. 《Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection》
No 10. 《DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints》
No 11. 《Augmenting Self-attention with Persistent Memory》
No 12. 《Semi-supervised Image Attribute Editing using Generative Adversarial Networks》
No 13. 《Neural Machine Reading Comprehension: Methods and Trends》
No 14. 《Inspirational Adversarial Image Generation》
No 15. 《Benign Overfitting in Linear Regression》
No 16. 《Benchmarking Model-Based Reinforcement Learning》
No 17. 《Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection》
No 18. 《GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation》
No 19. 《Fine-grained zero-shot recognition with metric rescaling》
No 20. 《The Difficulty of Training Sparse Neural Networks》
No 21. 《Brno Mobile OCR Dataset》
No 22. 《A Simple Deep Personalized Recommendation System》
No 23. 《Fast Training of Sparse Graph Neural Networks on Dense Hardware》
No 24. 《Learning Data Augmentation Strategies for Object Detection》
No 25. 《Complexity of Highly Parallel Non-Smooth Convex Optimization》
No 26. 《Attribute-Driven Spontaneous Motion in Unpaired Image Translation》
No 27. 《Style Generator Inversion for Image Enhancement and Animation》
No 28. 《Identifying Emotions from Walking using Affective and Deep Features》
No 29. 《Discovering Communities of Community Discovery》
No 30. 《Supervised Uncertainty Quantification for Segmentation with Multiple Annotations》

No 1. 《What graph neural networks cannot learn: depth vs width》
No 2. 【用无监督词向量从材料科学文献中获取潜在知识】
No 3. 【用无监督数据增扩推进半监督学习】
No 4. 《Adaptive Attention Span in Transformers》
No 5. 《Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty》
No 6. 《Slim-CNN: A Light-Weight CNN for Face Attribute Prediction》
No 7. 《Neural Networks, Hypersurfaces, and Radon Transforms》
No 8. 《Multivariate Time Series Imputation with Variational Autoencoders》
No 9. 《Discovering Communities of Community Discovery》
No 10. 《Large Scale Adversarial Representation Learning》
No 11. 《DeepMRSeg: A convolutional deep neural network for anatomy and abnormality segmentation on MR images》
No 12. 《Evolving the Hearthstone Meta》
No 13. 《Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning》
No 14. 《Video Crowd Counting via Dynamic Temporal Modeling》
No 15. 《Learning Markov models via low-rank optimization》
No 16. 《Mask Embedding in conditional GAN for Guided Synthesis of High Resolution Images》
No 17. 《Learning Landmarks from Unaligned Data using Image Translation》
No 18. 《Sparse Networks from Scratch: Faster Training without Losing Performance》
No 19. 《Curriculum Learning for Deep Generative Models with Clustering》
No 20. 《BAM! Born-Again Multi-Task Networks for Natural Language Understanding》
No 21. 《Guided Image Generation with Conditional Invertible Neural Networks》
No 22. 《M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention》
No 23. 《Variational Autoencoders and Nonlinear ICA: A Unifying Framework》
No 24. 《PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows》
No 25. 《BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs》
No 26. 《Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?》
No 27. 《Topic Modeling in Embedding Spaces》
No 28. 《A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks》
No 29. 《UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor》
No 30. 《MIDI-Sandwich: Multi-model Multi-task Hierarchical Conditional VAE-GAN networks for Symbolic Single-track Music Generation》

No 1. 《Graph Neural Networks: A Review of Methods and Applications》
No 2. 《R-Transformer: Recurrent Neural Network Enhanced Transformer》
No 3. 《Gated-SCNN: Gated Shape CNNs for Semantic Segmentation》
No 4. 《BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs》
No 5. 《Financial Time Series Data Processing for Machine Learning》
No 6. 《WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia》
No 7. 【“所见即所得”网络图布局:图布局深度生成模型】
No 8. 《Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology》
No 9. 《Topic Modeling in Embedding Spaces》
No 10. 【用Jupyter Notebooks实现可再现研究的十条简单规则】
No 11. 《A General Framework for Uncertainty Estimation in Deep Learning》
No 12. 《Large Memory Layers with Product Keys》
No 13. 《Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming》
No 14. 《Hello, It's GPT-2 -- How Can I Help You? Towards the Use of Pretrained Language Models for Task-Oriented Dialogue Systems》
No 15. 《Making AI Forget You: Data Deletion in Machine Learning》
No 16. 《Adversarial Objects Against LiDAR-Based Autonomous Driving Systems》
No 17. 《Knowledge Graph Embedding for Ecotoxicological Effect Prediction》
No 18. 《Efficient Video Generation on Complex Datasets》
No 19. 《Learning to learn with quantum neural networks via classical neural networks》
No 20. 《Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation》
No 21. 《Artificial Intelligence as a Services (AI-aaS) on Software-Defined Infrastructure》
No 22. 《Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning》
No 23. 《On the ''steerability' of generative adversarial networks》
No 24. 《Towards Understanding Generalization in Gradient-Based Meta-Learning》
No 25. 《k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport》
No 26. 《Implicit Regularization in Deep Matrix Factorization》
No 27. 《Zero-shot Learning for Audio-based Music Classification and Tagging》
No 28. 《The What-If Tool: Interactive Probing of Machine Learning Models》
No 29. 《Natural Adversarial Examples》
No 30. 《Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences》

No 1. 《Time2Vec: Learning a Vector Representation of Time》
No 2. 《SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications》
No 3. 《Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function》
No 4. 《Techniques for Automated Machine Learning》
No 5. 《A Baseline for 3D Multi-Object Tracking》
No 6. 《MixNet: Mixed Depthwise Convolutional Kernels》
No 7. 《Pairwise Link Prediction》
No 8. 《Quant GANs: Deep Generation of Financial Time Series》
No 9. 《Green AI》
No 10. 《Deep-SLAM++: Object-level RGBD SLAM based on class-specific deep shape priors》
No 11. 《NPA: Neural News Recommendation with Personalized Attention》
No 12. 《OmniNet: A unified architecture for multi-modal multi-task learning》
No 13. 《Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation》
No 14. 《Faster Neural Network Training with Data Echoing》
No 15. 《Image-and-Spatial Transformer Networks for Structure-Guided Image Registration》
No 16. 《Bayesian Inference with Generative Adversarial Network Priors》
No 17. 《Noise Contrastive Variational Autoencoders》
No 18. 《Understanding Video Content: Efficient Hero Detection and Recognition for the Game 'Honor of Kings'》
No 19. 《U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation》
No 20. 《Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images》
No 21. 《Spectral Analysis of Latent Representations》
No 22. 《IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification》
No 23. 《An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments》
No 24. 《Differentiable Bayesian Neural Network Inference for Data Streams》
No 25. 《Trusses and Trapezes: Easily-Interpreted Communities in Social Networks》
No 26. 《Y-Autoencoders: disentangling latent representations via sequential-encoding》
No 27. 《Convolutional Neural Networks on Randomized Data》
No 28. 《Learning to Select, Track, and Generate for Data-to-Text》
No 29. 《Hierarchical Sequence to Sequence Voice Conversion with Limited Data》
No 30. 《Statistical data analysis in the Wasserstein space》

No 1. 《Graph Neural Networks: A Review of Methods and Applications》
No 2. 《SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications》
No 3. 《Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches》
No 4. 《The Matrix Calculus You Need For Deep Learning》
No 5. 《Understanding Video Content: Efficient Hero Detection and Recognition for the Game 'Honor of Kings'》
No 6. 《DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks》
No 7. 《U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation》
No 8. 《Green AI》
No 9. 《Bridging the Gap between Training and Inference for Neural Machine Translation》
No 10. 《Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation》
No 11. 《Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview》
No 12. 《MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification》
No 13. 《RoBERTa: A Robustly Optimized BERT Pretraining Approach》
No 14. 《Learning to Select, Track, and Generate for Data-to-Text》
No 15. 《Deep Reinforcement Learning for Personalized Search Story Recommendation》
No 16. 《On Mutual Information Maximization for Representation Learning》
No 17. 《Eidetic 3D LSTM: A Model for Video Prediction and Beyond》
No 18. 《Don't Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation》
No 19. 《Lifelong GAN: Continual Learning for Conditional Image Generation》
No 20. 《Deep Gradient Boosting》
No 21. 《MaskGAN: Towards Diverse and Interactive Facial Image Manipulation》
No 22. 《iCartoonFace: A Benchmark of Cartoon Person Recognition》
No 23. 《EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks》
No 24. 《Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment》
No 25. 《Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs》
No 26. 《Towards meta-learning for multi-target regression problems》
No 27. 《Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking》
No 28. 《A Neural Network Based On-device Learning Anomaly Detector for Edge Devices》
No 29. 《Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems》
No 30. 《Music Recommendations in Hyperbolic Space: An Application of Empirical Bayes and Hierarchical Poincaré Embeddings》

No 1. 【(滴滴)深度价值网络多驾驶员订单调度方法】
No 2. 《Towards Explainable NLP: A Generative Explanation Framework for Text Classification》
No 3. 《Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview》
No 4. 《Optimizing Multi-GPU Parallelization Strategies for Deep Learning Training》
No 5. 【硕士论文:多说话人自动语音克隆】
No 6. 《hood2vec: Identifying Similar Urban Areas Using Mobility Networks》
No 7. 《FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation》
No 8. 《Grape detection, segmentation and tracking using deep neural networks and three-dimensional association》
No 9. 《A Simple and Effective Approach for Fine Tuning Pre-trained Word Embeddings for Improved Text Classification》
No 10. 《Machine Learning at the Network Edge: A Survey》
No 11. 《Structuring Autoencoders》
No 12. 《Sparse-to-Dense Hypercolumn Matching for Long-Term Visual Localization》
No 13. 《Invariance reduces Variance: Understanding Data Augmentation in Deep Learning and Beyond》
No 14. 《Composition-Aware Image Aesthetics Assessment》
No 15. 《ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks》
No 16. 《Learnability for the Information Bottleneck》
No 17. 《An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing》
No 18. 《ERNIE 2.0: A Continual Pre-training Framework for Language Understanding》
No 19. 《Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling》
No 20. 《Chainer: A Deep Learning Framework for Accelerating the Research Cycle》
No 21. 《How Good is SGD with Random Shuffling?》
No 22. 《Functional probabilistic programming for scalable Bayesian modelling》
No 23. 《Beyond BLEU: Training Neural Machine Translation with Semantic Similarity》
No 24. 《Bringing Giant Neural Networks Down to Earth with Unlabeled Data》
No 25. 《Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks》
No 26. 《Autoencoder-Based Incremental Class Learning without Retraining on Old Data》
No 27. 《PU-GAN: a Point Cloud Upsampling Adversarial Network》
No 28. 《Word2vec to behavior: morphology facilitates the grounding of language in machines》
No 29. 《Cross-Attention End-to-End ASR for Two-Party Conversations》
No 30. 《Robust Learning with Jacobian Regularization》

No 1. 《AutoML: A Survey of the State-of-the-Art》
No 2. 《Attention is not not Explanation》
No 3. 《How much data is sufficient to learn high-performing algorithms?》
No 4. 《Matrix Nets: A New Deep Architecture for Object Detection》
No 5. 《SqueezeNAS: Fast neural architecture search for faster semantic segmentation》
No 6. 《Anomaly Detection in High Dimensional Data》
No 7. 《metric-learn: Metric Learning Algorithms in Python》
No 8. 《Incremental Reinforcement Learning --- a New Continuous Reinforcement Learning Frame Based on Stochastic Differential Equation methods》
No 9. 《DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction》
No 10. 《One-shot Face Reenactment》
No 11. 《U-Net Fixed-Point Quantization for Medical Image Segmentation》
No 12. 《Predicting 3D Human Dynamics from Video》
No 13. 《VisualBERT: A Simple and Performant Baseline for Vision and Language》
No 14. 《LVIS: A Dataset for Large Vocabulary Instance Segmentation》
No 15. 《Self-supervised Learning for Video Correspondence Flow》
No 16. 《Linear Dynamics: Clustering without identification》
No 17. 《Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs》
No 18. 《Variational Bayes on Manifolds》
No 19. 《DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better》
No 20. 《Structured Knowledge Discovery from Massive Text Corpus》
No 21. 《Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds》
No 22. 《Self-supervised Attention Model for Weakly Labeled Audio Event Classification》
No 23. 《AdvFaces: Adversarial Face Synthesis》
No 24. 《Dimensionality Reduction Flows》
No 25. 《Learning Two-View Correspondences and Geometry Using Order-Aware Network》
No 26. 《Deep Learning for Detecting Building Defects Using Convolutional Neural Networks》
No 27. 《Learning a Unified Embedding for Visual Search at Pinterest》
No 28. 《Editing Text in the Wild》
No 29. 《Production Ranking Systems: A Review》
No 30. 《Modularity belief propagation on multilayer networks to detect significant community structure》

No 1. 《Recent Advances in Deep Learning for Object Detection》
No 2. 《Few-shot Text Classification with Distributional Signatures》
No 3. 《AmazonQA: A Review-Based Question Answering Task》
No 4. 《FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age》
No 5. 《Make a Face: Towards Arbitrary High Fidelity Face Manipulation》
No 6. 《AutoGAN: Neural Architecture Search for Generative Adversarial Networks》
No 7. 《Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss》
No 8. 《A Selective Overview of Deep Learning》
No 9. 《Multimodal Style Transfer via Graph Cuts》
No 10. 《Accelerated CNN Training Through Gradient Approximation》
No 11. 【包含知识、对抗性强的表示学习】
No 12. 《BERT Rediscovers the Classical NLP Pipeline》
No 13. 《Federated Learning: Challenges, Methods, and Future Directions》
No 14. 《SPA-GAN: Spatial Attention GAN for Image-to-Image Translation》
No 15. 【针对不可预见对抗攻击的鲁棒性测试】
No 16. 《iCassava 2019 Fine-Grained Visual Categorization Challenge》
No 17. 《ExtremeC3Net: Extreme Lightweight Portrait Segmentation Networks using Advanced C3-modules》
No 18. 《TunaGAN: Interpretable GAN for Smart Editing》
No 19. 《AutoCorrect: Deep Inductive Alignment of Noisy Geometric Annotations》
No 20. 《Saccader: Improving Accuracy of Hard Attention Models for Vision》
No 21. 《Causality from the Point of View of Classical Statistics》
No 22. 《Bayesian Inference for Large Scale Image Classification》
No 23. 《Adversarial Neural Pruning》
No 24. 《GLAMpoints: Greedily Learned Accurate Match points》
No 25. 《Importance of spatial predictor variable selection in machine learning applications -- Moving from data reproduction to spatial prediction》
No 26. 《One Model To Rule Them All》
No 27. 《NeuroMask: Explaining Predictions of Deep Neural Networks through Mask Learning》
No 28. 《A Multimodal Deep Network for the Reconstruction of T2W MR Images》
No 29. 《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》
No 30. 《Solar image denoising with convolutional neural networks》

No 1. 《Graph Neural Networks: A Review of Methods and Applications》
No 2. 《Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks》
No 3. 《Revealing the Dark Secrets of BERT》
No 4. 《Object detection on aerial imagery using CenterNet》
No 5. 《Visualizing and Understanding the Effectiveness of BERT》
No 6. 《Conditional Flow Variational Autoencoders for Structured Sequence Prediction》
No 7. 《Text Summarization with Pretrained Encoders》
No 8. 《ViCo: Word Embeddings from Visual Co-occurrences》
No 9. 【量子卷积神经网络】
No 10. 《Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning》
No 11. 《Generating High-Resolution Fashion Model Images Wearing Custom Outfits》
No 12. 《Theory and Evaluation Metrics for Learning Disentangled Representations》
No 13. 《Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning》
No 14. 《Transfer in Deep Reinforcement Learning using Knowledge Graphs》
No 15. 《The many faces of deep learning》
No 16. 《Lecture Notes: Selected topics on robust statistical learning theory》
No 17. 《From Community to Role-based Graph Embeddings》
No 18. 《Compositional Video Prediction》
No 19. 《A Probabilistic Representation of Deep Learning》
No 20. 《Football is becoming boring; Network analysis of 88 thousands matches in 11 major leagues》
No 21. 《Mocycle-GAN: Unpaired Video-to-Video Translation》
No 22. 《Learning Disentangled Representations via Independent Subspaces》
No 23. 《Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent》
No 24. 《AdvHat: Real-world adversarial attack on ArcFace Face ID system》
No 25. 《A Neural Network for Semi-Supervised Learning on Manifolds》
No 26. 《Local Unsupervised Learning for Image Analysis》
No 27. 《Detecting abnormalities in resting-state dynamics: An unsupervised learning approach》
No 28. 《Noise Flow: Noise Modeling with Conditional Normalizing Flows》
No 29. 《Two Decades of Network Science as seen through the co-authorship network of network scientists》
No 30. 《Dynamics-aware Embeddings》

No 1. 【Science封面文章:多人扑克AI】
No 2. 《Self-Supervised Representation Learning via Neighborhood-Relational Encoding》
No 3. 《Feature Gradients: Scalable Feature Selection via Discrete Relaxation》
No 4. 《Named Entity Recognition Only from Word Embeddings》
No 5. 《Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective》
No 6. 《DRD-Net: Detail-recovery Image Deraining via Context Aggregation Networks》
No 7. 《A Possible Reason for why Data-Driven Beats Theory-Driven Computer Vision》
No 8. 《Face-to-Parameter Translation for Game Character Auto-Creation》
No 9. 《ChipGAN: A Generative Adversarial Network for Chinese Ink Wash Painting Style Transfer》
No 10. 《Gradient Weighted Superpixels for Interpretability in CNNs》
No 11. 《Hierarchical Text Classification with Reinforced Label Assignment》
No 12. 《SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition》
No 13. 《EGNet:Edge Guidance Network for Salient Object Detection》
No 14. 《Reinforcement Learning: Prediction, Control and Value Function Approximation》
No 15. 《Language Models as Knowledge Bases?》
No 16. 《Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning》
No 17. 《Consistency of community structure in complex networks》
No 18. 《Two-Pass End-to-End Speech Recognition》
No 19. 《Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures》
No 20. 《Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention》
No 21. 《Deep Equilibrium Models》
No 22. 《Large Scale Landmark Recognition via Deep Metric Learning》
No 23. 《Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation》
No 24. 《Meta-Learning with Warped Gradient Descent》
No 25. 《CASIA-SURF: A Large-scale Multi-modal Benchmark for Face Anti-spoofing》
No 26. 《FACSIMILE: Fast and Accurate Scans From an Image in Less Than a Second》
No 27. 《Neural Snowball for Few-Shot Relation Learning》
No 28. 《Transfer Learning Between Related Tasks Using Expected Label Proportions》
No 29. 《Spectral Regularization for Combating Mode Collapse in GANs》
No 30. 《ORBSLAM-Atlas: a robust and accurate multi-map system》

No 1. 《Graph-based data clustering via multiscale community detection》
No 2. 《SoftTriple Loss: Deep Metric Learning Without Triplet Sampling》
No 3. 《Meta-Learning with Warped Gradient Descent》
No 4. 《爱可可老师一周论文精选(2019.9.7)》
No 5. 《DeepHealth: Deep Learning for Health Informatics》
No 6. 《Modeling User Reputation in Online Social Networks: The Role of Costs, Benefits, and Reciprocity》
No 7. 《FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow》
No 8. 《How Old Are You? Face Age Translation with Identity Preservation Using GANs》
No 9. 《Meta-Learning with Implicit Gradients》
No 10. 《A Convolutional Neural Network Approach Towards Self-Driving Cars》
No 11. 《End-to-End Conditional GAN-based Architectures for Image Colourisation》
No 12. 《A review of Approximate Bayesian Computation methods via density estimation: inference for simulator-models》
No 13. 《WaveGlow: A Flow-based Generative Network for Speech Synthesis》
No 14. 《Quasi-Newton Optimization Methods For Deep Learning Applications》
No 15. 《Explicit Facial Expression Transfer via Fine-Grained Semantic Representations》
No 16. 《Back to the Future -- Sequential Alignment of Text Representations》
No 17. 《Learning Action-Transferable Policy with Action Embedding》
No 18. 《Transfusion: Understanding Transfer Learning for Medical Imaging》
No 19. 《Discriminative Topic Modeling with Logistic LDA》
No 20. 《Mask-Predict: Parallel Decoding of Conditional Masked Language Models》
No 21. 《Set Flow: A Permutation Invariant Normalizing Flow》
No 22. 《Adaptively Sparse Transformers》
No 23. 《Higher-order Comparisons of Sentence Encoder Representations》
No 24. 《Best Practices for Scientific Research on Neural Architecture Search》
No 25. 《Graph Neural Networks: A Review of Methods and Applications》
No 26. 《Swapped Face Detection using Deep Learning and Subjective Assessment》
No 27. 《Quantum Natural Gradient》
No 28. 《Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement》
No 29. 《DeepPrivacy: A Generative Adversarial Network for Face Anonymization》
No 30. 《Neural Style-Preserving Visual Dubbing》

No 1. 《FreeAnchor: Learning to Match Anchors for Visual Object Detection》
No 2. 《Torchmeta: A Meta-Learning library for PyTorch》
No 3. 《PSGAN: Pose-Robust Spatial-Aware GAN for Customizable Makeup Transfer》
No 4. 《LSTM-Based Anomaly Detection: Detection Rules from Extreme Value Theory》
No 5. 《Do NLP Models Know Numbers? Probing Numeracy in Embeddings》
No 6. 《Controllable Text-to-Image Generation》
No 7. 《CvxNets: Learnable Convex Decomposition》
No 8. 《Reinforcement Learning and Video Games》
No 9. 《Performance Analysis and Comparison of Distributed Machine Learning Systems》
No 10. 《Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning》
No 11. 《Structured Query Construction via Knowledge Graph Embedding》
No 12. 《Intensity augmentation for domain transfer of whole breast segmentation in MRI》
No 13. 《Knowledge Enhanced Attention for Robust Natural Language Inference》
No 14. 《Specifying Object Attributes and Relations in Interactive Scene Generation》
No 15. 《Entity Projection via Machine-Translation for Cross-Lingual NER》
No 16. 《CUDA: Contradistinguisher for Unsupervised Domain Adaptation》
No 17. 《A Joint Learning and Communications Framework for Federated Learning over Wireless Networks》
No 18. 《A deep learning system for differential diagnosis of skin diseases》
No 19. 《RNN Architecture Learning with Sparse Regularization》
No 20. 《Unsupervised Eyeglasses Removal in the Wild》
No 21. 《3D Ken Burns Effect from a Single Image》
No 22. 《MetalGAN: a Cluster-based Adaptive Training for Few-Shot Adversarial Colorization》
No 23. 《Multi-mapping Image-to-Image Translation via Learning Disentanglement》
No 24. 《REGAL: Transfer Learning For Fast Optimization of Computation Graphs》
No 25. 《Learning to Deceive with Attention-Based Explanations》
No 26. 《Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models》
No 27. 《DurIAN: Duration Informed Attention Network For Multimodal Synthesis》
No 28. 《Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning》
No 29. 《FakeSpotter: A Simple Baseline for Spotting AI-Synthesized Fake Faces》
No 30. 《HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking》

No 1. 《Enriching BERT with Knowledge Graph Embeddings for Document Classification》
No 2. 《Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks》
No 3. 《Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning》
No 4. 《Reinforcement Learning for Portfolio Management》
No 5. 《Chargrid-OCR: End-to-end trainable Optical Character Recognition through Semantic Segmentation and Object Detection》
No 6. 《Data Augmentation Revisited: Rethinking the Distribution Gap between Clean and Augmented Data》
No 7. 《PyDEns: a Python Framework for Solving Differential Equations with Neural Networks》
No 8. 《Flight Controller Synthesis Via Deep Reinforcement Learning》
No 9. 《Unsupervised Learning for Real-World Super-Resolution》
No 10. 《Domain Aggregation Networks for Multi-Source Domain Adaptation》
No 11. 《Adversarial Attacks and Defenses in Images, Graphs and Text: A Review》
No 12. 《InterpretML: A Unified Framework for Machine Learning Interpretability》
No 13. 《Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models》
No 14. 《Zero-Shot Action Recognition in Videos: A Survey》
No 15. 《Synthetic Data for Deep Learning》
No 16. 《On Understanding Knowledge Graph Representation》
No 17. 《Attention Interpretability Across NLP Tasks》
No 18. 《Adaptive Scheduling for Multi-Task Learning》
No 19. 《Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making》
No 20. 《Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis》
No 21. 《A Full-Image Full-Resolution End-to-End-Trainable CNN Framework for Image Forgery Detection》
No 22. 《Quantum Graph Neural Networks》
No 23. 《Making the Invisible Visible: Action Recognition Through Walls and Occlusions》
No 24. 《Rapid Bayesian inference for expensive stochastic models》
No 25. 《Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML》
No 26. 《Human Synthesis and Scene Compositing》
No 27. 《Causal inference and machine learning approaches for evaluation of the health impacts of large-scale air quality regulations》
No 28. 《Feedback Learning for Improving the Robustness of Neural Networks》
No 29. 《Variational Conditional GAN for Fine-grained Controllable Image Generation》
No 30. 《Counterfactual Cross-Validation: Effective Causal Model Selection from Observational Data》

No 1. 《TinyBERT: Distilling BERT for Natural Language Understanding》
No 2. 《GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning》
No 3. 《Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection》
No 4. 《Hamiltonian Generative Networks》
No 5. 《Efficient Graph Generation with Graph Recurrent Attention Networks》
No 6. 《Extreme Language Model Compression with Optimal Subwords and Shared Projections》
No 7. 《DM M -Net: Differentiable Mask-Matching Network for Video Object Segmentation》
No 8. 《Quantum Graph Neural Networks》
No 9. 《Mathematical Reasoning in Latent Space》
No 10. 《The Differentiable Cross-Entropy Method》
No 11. 《Compiler-Level Matrix Multiplication Optimization for Deep Learning》
No 12. 《Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle》
No 13. 《A Theoretical Analysis of the Number of Shots in Few-Shot Learning》
No 14. 《InceptionTime: Finding AlexNet for Time Series Classification》
No 15. 《Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks》
No 16. 《DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter》
No 17. 《Overparameterized Neural Networks Can Implement Associative Memory》
No 18. 《DeepView: Visualizing the behavior of deep neural networks in a part of the data space》
No 19. 《Neural Text Generation with Unlikelihood Training》
No 20. 《Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold》
No 21. 《Manifold Forests: Closing the Gap on Neural Networks》
No 22. 《DOOR-SLAM: Distributed, Online, and Outlier Resilient SLAM for Robotic Teams》
No 23. 《Machine Learning for Clinical Predictive Analytics》
No 24. 《RLBench: The Robot Learning Benchmark & Learning Environment》
No 25. 《Dialogue Transformers》
No 26. 《Adversarial Examples for Deep Learning Cyber Security Analytics》
No 27. 《Unsupervised Generative 3D Shape Learning from Natural Images》
No 28. 《Deep learning tools for the measurement of animal behavior in neuroscience》
No 29. 《A Mean-Field Theory for Kernel Alignment with Random Features in Generative Adversarial Networks》
No 30. 《Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data》

No 1. 【DexPilot:基于视觉的灵巧机械手系统远程操作】
No 2. 《YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection》
No 3. 《Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization》
No 4. 《Transformers: State-of-the-art Natural Language Processing》
No 5. 《Recommending what video to watch next: a multitask ranking system》
No 6. 《Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation》
No 7. 《Fast Panoptic Segmentation Network》
No 8. 《Accelerating Data Loading in Deep Neural Network Training》
No 9. 《Stabilizing Generative Adversarial Network Training: A Survey》
No 10. 《Semi Few-Shot Attribute Translation》
No 11. 《Entropy Penalty: Towards Generalization Beyond the IID Assumption》
No 12. 《TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction》
No 13. 《A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks》
No 14. 【用经典机器学习改进量子计算】
No 15. 《Large Scale Adversarial Representation Learning》
No 16. 《Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop》
No 17. 《Kornia: an Open Source Differentiable Computer Vision Library for PyTorch》
No 18. 《DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter》
No 19. 《TorchBeast: A PyTorch Platform for Distributed RL》
No 20. 《'I'm sorry Dave, I'm afraid I can't do that' Deep Q-learning from forbidden action》
No 21. 《Detecting Deception in Political Debates Using Acoustic and Textual Features》
No 22. 《OpenVSLAM: A Versatile Visual SLAM Framework》
No 23. 《Distilling importance sampling》
No 24. 《Applying Deep Learning To Airbnb Search》
No 25. 《What Does 2D Geometric Information Really Tell Us About 3D Face Shape?》
No 26. 《Neural Network Applications in Earthquake Prediction (1994-2019): Meta-Analytic Insight on their Limitations》
No 27. 《Is Fast Adaptation All You Need?》
No 28. 《Open Set Medical Diagnosis》
No 29. 《Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction》
No 30. 《Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs》

No 1. 《Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters》
No 2. 《DeepGCNs: Making GCNs Go as Deep as CNNs》
No 3. 《Link Prediction via Deep Learning》
No 4. 《Deep Markov Chain Monte Carlo》
No 5. 《Graph Few-shot Learning via Knowledge Transfer》
No 6. 《More Powerful Selective Kernel Tests for Feature Selection》
No 7. 《All of Linear Regression》
No 8. 《A Simple Randomization Technique for Generalization in Deep Reinforcement Learning》
No 9. 《NGBoost: Natural Gradient Boosting for Probabilistic Prediction》
No 10. 《exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformers Models》
No 11. 《Deep Kernel Transfer in Gaussian Processes for Few-shot Learning》
No 12. 《Towards Object Detection from Motion》
No 13. 《Adversarial Training: embedding adversarial perturbations into the parameter space of a neural network to build a robust system》
No 14. 《Transformers without Tears: Improving the Normalization of Self-Attention》
No 15. 《A Comparison Study on Nonlinear Dimension Reduction Methods with Kernel Variations: Visualization, Optimization and Classification》
No 16. 《Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods》
No 17. 《BoTorch: Programmable Bayesian Optimization in PyTorch》
No 18. 《ANDA: A Novel Data Augmentation Technique Applied to Salient Object Detection》
No 19. 《Understanding the Limitations of Variational Mutual Information Estimators》
No 20. 《Stabilizing Transformers for Reinforcement Learning》
No 21. 《Combining Geometric and Topological Information in Image Segmentation》
No 22. 《Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs》
No 23. 《Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions》
No 24. 《The Rényi Gaussian Process》
No 25. 《Fluid Flow Mass Transport for Generative Networks》
No 26. 《Prescribed Generative Adversarial Networks》
No 27. 《Learning Dense Wide Baseline Stereo Matching for People》
No 28. 《Deep Evidential Regression》
No 29. 《Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations》
No 30. 《ES-MAML: Simple Hessian-Free Meta Learning》

No 1. 《Gradient Boosted Decision Tree Neural Network》
No 2. 《Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations》
No 3. 《Universal Text Representation from BERT: An Empirical Study》
No 4. 《Mixed Pooling Multi-View Attention Autoencoder for Representation Learning in Healthcare》
No 5. 《Improving the Gating Mechanism of Recurrent Neural Networks》
No 6. 《Component Attention Guided Face Super-Resolution Network: CAGFace》
No 7. 《Q8BERT: Quantized 8Bit BERT》
No 8. 《Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge》
No 9. 《Sequence-to-sequence Singing Synthesis Using the Feed-forward Transformer》
No 10. 《An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation》
No 11. 《Causal bootstrapping》
No 12. 《Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks》
No 13. 《Winning the ICCV 2019 Learning to Drive Challenge》
No 14. 《Neural Logic Networks》
No 15. 《MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction》
No 16. 《Learning Partial Differential Equations from Data Using Neural Networks》
No 17. 《LinesToFacePhoto: Face Photo Generation from Lines with Conditional Self-Attention Generative Adversarial Network》
No 18. 《The Distributed Bloom Filter》
No 19. 《gradSLAM: Dense SLAM meets Automatic Differentiation》
No 20. 《AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects》
No 21. 《Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI》
No 22. 《A Mutual Information Maximization Perspective of Language Representation Learning》
No 23. 《Meta-Learning Deep Energy-Based Memory Models》
No 24. 《DwNet: Dense warp-based network for pose-guided human video generation》
No 25. 《Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules》
No 26. 《Iterative Matching Point》
No 27. 《Planning for Goal-Oriented Dialogue Systems》
No 28. 《Supervised Encoding for Discrete Representation Learning》
No 29. 《Gaze360: Physically Unconstrained Gaze Estimation in the Wild》
No 30. 《Real-world attack on MTCNN face detection system》

No 1. 【少样本视频到视频合成:人体骨架、涂鸦、街景分割图的逼真视频合成】
No 2. 【YOLACT实时实例分割】
No 3. 《Deep Semantic Segmentation of Natural and Medical Images: A Review》
No 4. 《SinGAN: Learning a Generative Model from a Single Natural Image》
No 5. 《Structured Low-Rank Algorithms: Theory, MR Applications, and Links to Machine Learning》
No 6. 《AI Benchmark: All About Deep Learning on Smartphones in 2019》
No 7. 【可微凸优化层】
No 8. 《Deep Learning vs. Traditional Computer Vision》
No 9. 《A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?》
No 10. 《Poisson CNN: Convolutional Neural Networks for the Solution of the Poisson Equation with Varying Meshes and Dirichlet Boundary Conditions》
No 11. 《Newton vs the machine: solving the chaotic three-body problem using deep neural networks》
No 12. 《Guided Image-to-Image Translation with Bi-Directional Feature Transformation》
No 13. 《Seeing What a GAN Cannot Generate》
No 14. 《BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension》
No 15. 《Scalable Deep Neural Networks via Low-Rank Matrix Factorization》
No 16. 《Multi-Stage Document Ranking with BERT》
No 17. 《Weakly-supervised Deep Anomaly Detection with Pairwise Relation Learning》
No 18. 《HUBERT Untangles BERT to Improve Transfer across NLP Tasks》
No 19. 《Weakly Supervised Disentanglement with Guarantees》
No 20. 《Consistency Regularization for Generative Adversarial Networks》
No 21. 《Multiplayer AlphaZero》
No 22. 《Supervised Encoding for Discrete Representation Learning》
No 23. 《Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning》
No 24. 《Learning Disentangled Representations for Recommendation》
No 25. 《H-VECTORS: Utterance-level Speaker Embedding Using A Hierarchical Attention Model》
No 26. 《MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences》
No 27. 《Landmark Ordinal Embedding》
No 28. 《Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports》
No 29. 《Learning to Predict Without Looking Ahead: World Models Without Forward Prediction》
No 30. 《Adversarial NLI: A New Benchmark for Natural Language Understanding》

No 1. 《Understanding the Role of Momentum in Stochastic Gradient Methods》
No 2. 【今日焦点:深度学习的批判性评价——深度学习离通用智能还很远的十大原因】
No 3. 《Confident Learning: Estimating Uncertainty in Dataset Labels》
No 4. 《The Measure of Intelligence》
No 5. 《Gradient-based Adaptive Markov Chain Monte Carlo》
No 6. 《Learning Without Loss》
No 7. 《Multi-Stage Document Ranking with BERT》
No 8. 《Fast Transformer Decoding: One Write-Head is All You Need》
No 9. 《Bayesian Decision Models: A Primer - ScienceDirect》
No 10. 《High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks》
No 11. 《Deep Learning for Stock Selection Based on High Frequency Price-Volume Data》
No 12. 《Continual Unsupervised Representation Learning》
No 13. 《Learning Disentangled Representations for Recommendation》
No 14. 《Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications》
No 15. 《The Deepfake Detection Challenge (DFDC) Preview Dataset》
No 16. 《Spatiotemporal Tile-based Attention-guided LSTMs for Traffic Video Prediction》
No 17. 《FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task Learning》
No 18. 《Learning Data Manipulation for Augmentation and Weighting》
No 19. 《Unsupervised Multi-Domain Multimodal Image-to-Image Translation with Explicit Domain-Constrained Disentanglement》
No 20. 《Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning》
No 21. 《Generalization through Memorization: Nearest Neighbor Language Models》
No 22. 《Adversarial NLI: A New Benchmark for Natural Language Understanding》
No 23. 《How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods》
No 24. 《Information Geometry of the Probability Simplex: A Short Course》
No 25. 【YOLACT实时实例分割】
No 26. 《Self-supervised Moving Vehicle Tracking with Stereo Sound》
No 27. 《Deep Learning of Subsurface Flow via Theory-guided Neural Network》
No 28. 《Attacking Optical Flow》
No 29. 《Dancing to Music》
No 30. 《Kernelized Bayesian Softmax for Text Generation》

No 1. 《On the Relationship between Self-Attention and Convolutional Layers》
No 2. 《Deep Learning for Stock Selection Based on High Frequency Price-Volume Data》
No 3. 《Confident Learning: Estimating Uncertainty in Dataset Labels》
No 4. 《Adversarial Fisher Vectors for Unsupervised Representation Learning》
No 5. 《Stacked Capsule Autoencoders》
No 6. 《Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research》
No 7. 《Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation》
No 8. 《Document-level Neural Machine Translation with Inter-Sentence Attention》
No 9. 《Recurrent Neural Network Transducer for Audio-Visual Speech Recognition》
No 10. 《The Measure of Intelligence》
No 11. 《Information Bottleneck Methods on Convolutional Neural Networks》
No 12. 《This dataset does not exist: training models from generated images》
No 13. 《How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods》
No 14. 《Probing the robustness of nested multi-layer networks》
No 15. 《Conversation Generation with Concept Flow》
No 16. 《DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning》
No 17. 《Self-training with Noisy Student improves ImageNet classification》
No 18. 《MLPerf Inference Benchmark》
No 19. 《What Do We Really Need? Degenerating U-Net on Retinal Vessel Segmentation》
No 20. 《Learning Internal Representations》
No 21. 《Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods》
No 22. 《HDBSCAN(ε̂ ): An Alternative Cluster Extraction Method for HDBSCAN》
No 23. 《CartoonRenderer: An Instance-based Multi-Style Cartoon Image Translator》
No 24. 《Modern Neural Networks Generalize on Small Data Sets》
No 25. 《360SD-Net: 360° Stereo Depth Estimation with Learnable Cost Volume》
No 26. 《Designing neural networks through neuroevolution | Nature Machine Intelligence》
No 27. 《Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models》
No 28. 《Nonlinearity + Networks: A 2020 Vision》
No 29. 《Emerging Cross-lingual Structure in Pretrained Language Models》
No 30. 《Evaluating Combinatorial Generalization in Variational Autoencoders》

No 1. 【BodyPix(2.0):TensorFlow.js 实现的浏览器里的实时人体图像分割】
No 2. 《Text classification with pixel embedding》
No 3. 《Basic Principles of Clustering Methods》
No 4. 《CenterMask : Real-Time Anchor-Free Instance Segmentation》
No 5. 《EfficientDet: Scalable and Efficient Object Detection》
No 6. 《EdgeNet: Balancing Accuracy and Performance for Edge-based Convolutional Neural Network Object Detectors》
No 7. 《Real-Time Reinforcement Learning》
No 8. 《GLMNet: Graph Learning-Matching Networks for Feature Matching》
No 9. 《There is Limited Correlation between Coverage and Robustness for Deep Neural Networks》
No 10. 《GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs》
No 11. 《Self-labelling via simultaneous clustering and representation learning》
No 12. 《MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets》
No 13. 《Rethinking deep active learning: Using unlabeled data at model training》
No 14. 《Random walks on hypergraphs》
No 15. 《Momentum Contrast for Unsupervised Visual Representation Learning》
No 16. 《The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design》
No 17. 《CartoonRenderer: An Instance-based Multi-Style Cartoon Image Translator》
No 18. 《Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game》
No 19. 《Faster AutoAugment: Learning Augmentation Strategies using Backpropagation》
No 20. 《Solving machine learning optimization problems using quantum computers》
No 21. 《Hierarchical Graph Pooling with Structure Learning》
No 22. 《Dynamic Instance Normalization for Arbitrary Style Transfer》
No 23. 《Compressive Transformers for Long-Range Sequence Modelling》
No 24. 《RandAugment: Practical automated data augmentation with a reduced search space》
No 25. 《Live Face De-Identification in Video》
No 26. 《Generate (non-software) Bugs to Fool Classifiers》
No 27. 《Self-supervised Learning of 3D Objects from Natural Images》
No 28. 《A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging》
No 29. 《Additive Bayesian Network Modelling with the R Package abn》
No 30. 《How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions》

No 1. 《Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator》
No 2. 《Graph Transformer Networks》
No 3. 《Representation Learning: A Statistical Perspective》
No 4. 《Bayesian forecasting of multivariate time series: Scalability, structure uncertainty and decisions》
No 5. 《AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks》
No 6. 《Image2StyleGAN++: How to Edit the Embedded Images?》
No 7. 【哎呀!视频里的意外行为检测】
No 8. 《TimeCaps: Capturing Time Series Data with Capsule Networks》
No 9. 《Semantic Bottleneck Scene Generation》
No 10. 《SuperGlue: Learning Feature Matching with Graph Neural Networks》
No 11. 《Learning to Communicate in Multi-Agent Reinforcement Learning : A Review》
No 12. 《Causality for Machine Learning》
No 13. 《Active Learning for Deep Detection Neural Networks》
No 14. 《Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding》
No 15. 《Differentiable Convex Optimization Layers》
No 16. 《Deep Motion Blur Removal Using Noisy/Blurry Image Pairs》
No 17. 《Instance Cross Entropy for Deep Metric Learning》
No 18. 《How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions》
No 19. 《Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis》
No 20. 《Bayesian interpretation of SGD as Ito process》
No 21. 《Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering》
No 22. 《Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild》
No 23. 《Parallelising MCMC via Random Forests》
No 24. 《Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach》
No 25. 《Towards a complete 3D morphable model of the human head》
No 26. 《Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models》
No 27. 《Compressing Representations for Embedded Deep Learning》
No 28. 《Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting》
No 29. 《Object-Guided Instance Segmentation for Biological Images》
No 30. 《Noise Robust Generative Adversarial Networks》

No 1. 《How to Fine-Tune BERT for Text Classification?》
No 2. 《PyTorch: An Imperative Style, High-Performance Deep Learning Library》
No 3. 《An Alternative Cross Entropy Loss for Learning-to-Rank》
No 4. 《Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019》
No 5. 《LaFIn: Generative Landmark Guided Face Inpainting》
No 6. 《All you need is a good representation: A multi-level and classifier-centric representation for few-shot learning》
No 7. 《Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks》
No 8. 《Learning Spatial Fusion for Single-Shot Object Detection》
No 9. 《Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task》
No 10. 《The Matrix Calculus You Need For Deep Learning》
No 11. 《StarGAN v2: Diverse Image Synthesis for Multiple Domains》
No 12. 《Mixing autoencoder with classifier: conceptual data visualization》
No 13. 《How Can We Know What Language Models Know?》
No 14. 《Fast Sparse ConvNets》
No 15. 《AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty》
No 16. 《Noise Robust Generative Adversarial Networks》
No 17. 《Full-Gradient Representation for Neural Network Visualization》
No 18. 《PlantDoc: A Dataset for Visual Plant Disease Detection》
No 19. 《What's Hidden in a Randomly Weighted Neural Network?》
No 20. 《Adversarial Examples Improve Image Recognition》
No 21. 《Lower Bounds for Non-Convex Stochastic Optimization》
No 22. 《ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring》
No 23. 《Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability》
No 24. 《Transflow Learning: Repurposing Flow Models Without Retraining》
No 25. 《Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment》
No 26. 《Neural Integration of Continuous Dynamics》
No 27. 《MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning》
No 28. 《In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction from 2D Landmarks》
No 29. 《Dynamic Portfolio Management with Reinforcement Learning》
No 30. 《Region segmentation via deep learning and convex optimization》

No 1. 《Dynamic Convolution: Attention over Convolution Kernels》
No 2. 【用大规模深度强化学习挑战Dota 2:OpenAI Five 如何打败世界冠军(Team OG)】
No 3. 《Recurrent Neural Networks (RNNs): A gentle Introduction and Overview》
No 4. 《AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty》
No 5. 《Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey》
No 6. 《Deep Learning for Visual Tracking: A Comprehensive Survey》
No 7. 《Why ADAM Beats SGD for Attention Models》
No 8. 《Meta-Learning without Memorization》
No 9. 《Single Sample Feature Importance: An Interpretable Algorithm for Low-Level Feature Analysis》
No 10. 《The Group Loss for Deep Metric Learning》
No 11. 《Multimodal Self-Supervised Learning for Medical Image Analysis》
No 12. 《Manifold Markov chain Monte Carlo methods for Bayesian inference in a wide class of diffusion models》
No 13. 《Self-Supervised 3D Keypoint Learning for Ego-motion Estimation》
No 14. 《Encoding Musical Style with Transformer Autoencoders》
No 15. 《Full-Gradient Representation for Neural Network Visualization》
No 16. 《Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection》
No 17. 《15 Keypoints Is All You Need》
No 18. 《Lower Bounds for Non-Convex Stochastic Optimization》
No 19. 《Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One》
No 20. 《Digital Twin: Acquiring High-Fidelity 3D Avatar from a Single Image》
No 21. 《Noise2Blur: Online Noise Extraction and Denoising》
No 22. 《Deep Ensembles: A Loss Landscape Perspective》
No 23. 《Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions》
No 24. 《Learning to Predict Explainable Plots for Neural Story Generation》
No 25. 《Face Beautification: Beyond Makeup Transfer》
No 26. 《Geometric Capsule Autoencoders for 3D Point Clouds》
No 27. 《Putting An End to End-to-End: Gradient-Isolated Learning of Representations》
No 28. 《12-in-1: Multi-Task Vision and Language Representation Learning》
No 29. 《Advances and Open Problems in Federated Learning》
No 30. 《Learning a Neural 3D Texture Space from 2D Exemplars》

No 1. 【用大规模深度强化学习挑战Dota 2:OpenAI Five 如何打败世界冠军(Team OG)】
No 2. 《UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation》
No 3. 《Recurrent Neural Networks (RNNs): A gentle Introduction and Overview》
No 4. 【来了~ PS强化学习环境】
No 5. 《From Reinforcement Learning to Optimal Control: A unified framework for sequential decisions》
No 6. 《Towards Explainable Deep Neural Networks (xDNN)》
No 7. 《Image Processing Using Multi-Code GAN Prior》
No 8. 《Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection》
No 9. 《Encoding Musical Style with Transformer Autoencoders》
No 10. 《Finding Missing Children: Aging Deep Face Features》
No 11. 《The Wasserstein-Fourier Distance for Stationary Time Series》
No 12. 《YOLACT++: Better Real-time Instance Segmentation》
No 13. 《Music-oriented Dance Video Synthesis with Pose Perceptual Loss》
No 14. 《Measuring Social Bias in Knowledge Graph Embeddings》
No 15. 《Asymmetric Generative Adversarial Networks for Image-to-Image Translation》
No 16. 《ManiGAN: Text-Guided Image Manipulation》
No 17. 《Inducing Relational Knowledge from BERT》
No 18. 《CG-GAN: An Interactive Evolutionary GAN-based Approach for Facial Composite Generation)》
No 19. 《Optimization for deep learning: theory and algorithms》
No 20. 《The Use of Deep Learning for Symbolic Integration: A Review of (Lample and Charton, 2019)》
No 21. 《Learning Structure-Appearance Joint Embedding for Indoor Scene Image Synthesis》
No 22. 《A Deep Neural Network's Loss Surface Contains Every Low-dimensional Pattern》
No 23. 《UNAS: Differentiable Architecture Search Meets Reinforcement Learning》
No 24. 《DeepDeform: Learning Non-rigid RGB-D Reconstruction with Semi-supervised Data》
No 25. 《Neural Voice Puppetry: Audio-driven Facial Reenactment》
No 26. 《More Data Can Hurt for Linear Regression: Sample-wise Double Descent》
No 27. 《Unconstrained Facial Expression Transfer using Style-based Generator》
No 28. 《Optimizing Rank-based Metrics with Blackbox Differentiation》
No 29. 《Cooperative Reasoning on Knowledge Graph and Corpus: A Multi-agentReinforcement Learning Approach》
No 30. 《Learning To Reach Goals Without Reinforcement Learning》

No 1. 《A literature survey of matrix methods for data science》
No 2. 《Optimization for deep learning: theory and algorithms》
No 3. 《Are Transformers universal approximators of sequence-to-sequence functions?》
No 4. 《Generating Positive Bounding Boxes for Balanced Training of Object Detectors》
No 5. 《PointRend: Image Segmentation as Rendering》
No 6. 《Deep Audio Prior》
No 7. 《Adversarial Representation Active Learning》
No 8. 《Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation》
No 9. 《ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language》
No 10. 《Measuring Dataset Granularity》
No 11. 《Mastering Complex Control in MOBA Games with Deep Reinforcement Learning》
No 12. 《Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction》
No 13. 《DeepSFM: Structure From Motion Via Deep Bundle Adjustment》
No 14. 《Early Detection of Research Trends》
No 15. 《Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax》
No 16. 《Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining》
No 17. 《Continuous Meta-Learning without Tasks》
No 18. 《Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve》
No 19. 《secml: A Python Library for Secure and Explainable Machine Learning》
No 20. 《AutoScale: Learning to Scale for Crowd Counting》
No 21. 《Learning a Spatio-Temporal Embedding for Video Instance Segmentation》
No 22. 《UMAP does not preserve global structure any better than t-SNE when using the same initialization》
No 23. 《Audio-Visual Embodied Navigation》
No 24. 《Topic subject creation using unsupervised learning for topic modeling》
No 25. 《Molecular Generative Model Based On Adversarially Regularized Autoencoder》
No 26. 《Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision》
No 27. 《Learning Singing From Speech》
No 28. 《RPGAN: GANs Interpretability via Random Routing》
No 29. 《CNN-generated images are surprisingly easy to spot... for now》
No 30. 《Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network》

No 1. 《A Gentle Introduction to Deep Learning for Graphs》
No 2. 《Deep Graph Similarity Learning: A Survey》
No 3. 【乳腺癌AI筛查系统评估:在筛查中AI系统能比专家更准确地发现乳腺癌】
No 4. 《Efficient Probabilistic Logic Reasoning with Graph Neural Networks》
No 5. 《Deep Learning in Medical Image Registration: A Review》
No 6. 《Reformer: The Efficient Transformer》
No 7. 《Deep Learning for 3D Point Clouds: A Survey》
No 8. 《Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport》
No 9. 《DeepHashing using TripletLoss》
No 10. 《Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve》
No 11. 《IS Attention All What You Need? -- An Empirical Investigation on Convolution-Based Active Memory and Self-Attention》
No 12. 《B-Spline CNNs on Lie groups》
No 13. 《Hamiltonian Generative Networks》
No 14. 《On the Difference Between the Information Bottleneck and the Deep Information Bottleneck》
No 15. 《OneGAN: Simultaneous Unsupervised Learning of Conditional Image Generation, Foreground Segmentation, and Fine-Grained Clustering》
No 16. 《Effective Data Augmentation with Multi-Domain Learning GANs》
No 17. 《Learning Robust Representations via Multi-View Information Bottleneck》
No 18. 《Detecting GAN generated errors》
No 19. 《Machine Learning from a Continuous Viewpoint》
No 20. 《FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping》
No 21. 《Smoothness and Stability in GANs》
No 22. 《Learning 3D Human Shape and Pose from Dense Body Parts》
No 23. 《Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity》
No 24. 《Neural Module Networks for Reasoning over Text》
No 25. 《Causally Correct Partial Models for Reinforcement Learning》
No 26. 《Graph Neural Networks Exponentially Lose Expressive Power for Node Classification》
No 27. 《Making Sense of Reinforcement Learning and Probabilistic Inference》
No 28. 《Semi-Supervised Generative Modeling for Controllable Speech Synthesis》
No 29. 《Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning》
No 30. 《The Chi-Square Test of Distance Correlation》

No 1. 《End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models》
No 2. 《A General and Adaptive Robust Loss Function》
No 3. 《Quantum Adversarial Machine Learning》
No 4. 《DeepHuman: 3D Human Reconstruction From a Single Image》
No 5. 《Beyond BLEU:Training Neural Machine Translation with Semantic Similarity》
No 6. 《Computational model discovery with reinforcement learning》
No 7. 《Semi-Supervised Learning with Normalizing Flows》
No 8. 《Randomly Projected Additive Gaussian Processes for Regression》
No 9. 《Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning》
No 10. 《CondConv: Conditionally Parameterized Convolutions for Efficient Inference》
No 11. 《From Research to Production and Back: Ludicrously Fast Neural Machine Translation》
No 12. 《Sea-Thru: A Method for Removing Water From Underwater Images》
No 13. 《Comparing Fine-tuning and Rewinding in Neural Network Pruning》
No 14. 《Gradient L1 Regularization for Quantization Robustness》
No 15. 《InverseRenderNet: Learning Single Image Inverse Rendering》
No 16. 《TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising》
No 17. 《MVTec AD -- A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection》
No 18. 《Unsupervised pre-training for sequence to sequence speech recognition》
No 19. 《From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction》
No 20. 《Disentangling Factors of Variations Using Few Labels》
No 21. 《Spectral Metric for Dataset Complexity Assessment》
No 22. 《The Myth of Double-Blind Review Revisited: ACL vs. EMNLP》
No 23. 《A Gentle Introduction to Deep Learning for Graphs》
No 24. 《Deep Graph Similarity Learning: A Survey》
No 25. 《On Bonus Based Exploration Methods In The Arcade Learning Environment》
No 26. 《MLPerf Training Benchmark》
No 27. 《Improving Deep Neuroevolution via Deep Innovation Protection》
No 28. 《Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity》
No 29. 《MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning》
No 30. 《Interdisciplinary Relationships Between Biological and Physical Sciences》

No 1. 《On the 'steerability' of generative adversarial networks》
No 2. 《Multi-Graph Transformer for Free-Hand Sketch Recognition》
No 3. 《Variational Autoencoders and Nonlinear ICA: A Unifying Framework》
No 4. 《Action Genome: Actions as Composition of Spatio-temporal Scene Graphs》
No 5. 《Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models》
No 6. 《Word contexts enhance the neural representation of individual letters in early visual cortex | Nature Communications》
No 7. 《Energy and Policy Considerations for Deep Learning in NLP》
No 8. 《Differentiable Reasoning on Large Knowledge Bases and Natural Language》
No 9. 《IGNOR: Image-guided Neural Object Rendering》
No 10. 《Programmatically Interpretable Reinforcement Learning》
No 11. 《Attention Privileged Reinforcement Learning For Domain Transfer》
No 12. 《Towards a complete 3D morphable model of the human head》
No 13. 《Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning》
No 14. 《Off-the-Shelf Unsupervised NMT》
No 15. 《LaFIn: Generative Landmark Guided Face Inpainting》
No 16. 《Interdisciplinary Relationships Between Biological and Physical Sciences》
No 17. 《B-Spline CNNs on Lie groups》
No 18. 《Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve》
No 19. 《Solar image denoising with convolutional neural networks》
No 20. 《SPA-GAN: Spatial Attention GAN for Image-to-Image Translation》
No 21. 《Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference》
No 22. 《How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift)》
No 23. 《Laplacian Smoothing Gradient Descent》
No 24. 《Aspect Specific Opinion Expression Extraction using Attention based LSTM-CRF Network》
No 25. 《Recurrent Entity Networks with Delayed Memory Update for Targeted Aspect-based Sentiment Analysis》
No 26. 《Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised》
No 27. 《Optuna: A Next-generation Hyperparameter Optimization Framework》
No 28. 《Randomly Projected Additive Gaussian Processes for Regression》
No 29. 《oLMpics -- On what Language Model Pre-training Captures》
No 30. 《Why ADAM Beats SGD for Attention Models》

No 1. 《A Causal View on Robustness of Neural Networks | OpenReview》
No 2. 《Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned》
No 3. 《The Story of Heads》
No 4. 《Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem | OpenReview》
No 5. 《FreeLB: Enhanced Adversarial Training for Language Understanding | OpenReview》
No 6. 《Recurrent Hierarchical Topic-Guided Neural Language Models | OpenReview》
No 7. 《Gradient L1 Regularization for Quantization Robustness》
No 8. 《Programmatically Interpretable Reinforcement Learning》
No 9. 《CATER: A diagnostic dataset for Compositional Actions & TEmporal Reasoning | OpenReview》
No 10. 《Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering》
No 11. 《What does it mean to solve the problem of discrimination in hiring? Social, technical and legal perspectives from the UK on automated hiring systems》
No 12. 《A Theory of Usable Information under Computational Constraints | OpenReview》
No 13. 《All-in-One Image-Grounded Conversational Agents》
No 14. 《Deep Graph Similarity Learning: A Survey》
No 15. 《Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems》
No 16. 《Dynamic Portfolio Management with Reinforcement Learning》
No 17. 《DeePCCI: Deep Learning-based Passive Congestion Control Identification》
No 18. 【可扩展肌肉驱动人体模拟与控制(SIGGRAPH 2019):深度强化学习运动模拟,基于全身肌肉骨骼模型,包含346块肌肉,可进行术后步态预测模拟】
No 19. 《Self-Supervised Learning of Pretext-Invariant Representations》
No 20. 《Winning Solution on LPIRC-ll Competition》
No 21. 【Airbnb动态定价的定制回归模型】
No 22. 《GenDICE: Generalized Offline Estimation of Stationary Values | OpenReview》
No 23. 《Reinforcement learning for bandwidth estimation and congestion control in real-time communications》
No 24. 《CenterMask : Real-Time Anchor-Free Instance Segmentation》
No 25. 《UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation》
No 26. 《Smoothness and Stability in GANs》
No 27. 《BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle》
No 28. 《Low-Memory Neural Network Training: A Technical Report》
No 29. 《Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning》
No 30. 《A Probabilistic U-Net for Segmentation of Ambiguous Images》

No 1. 《Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding》
No 2. 《Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation》
No 3. 《Bayesian Reasoning with Deep-Learned Knowledge》
No 4. 《Multi-Level Representation Learning for Deep Subspace Clustering》
No 5. 《A CNN With Multi-scale Convolution for Hyperspectral Image Classification using Target-Pixel-Orientation scheme》
No 6. 《Semantic Sensitive TF-IDF to Determine Word Relevance in Documents》
No 7. 《Multi-label Prediction in Time Series Data using Deep Neural Networks》
No 8. 《ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation》
No 9. 《Semantics-aware BERT for Language Understanding》
No 10. 《A Primer on Domain Adaptation》
No 11. 《stream-learn -- open-source Python library for difficult data stream batch analysis》
No 12. 《ERA: A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos》
No 13. 《Going beyond accuracy: estimating homophily in social networks using predictions》
No 14. 《Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles》
No 15. 《Universal Data Anomaly Detection via Inverse Generative Adversary Network》
No 16. 《Pop Music Transformer: Generating Music with Rhythm and Harmony》
No 17. 《Proving the Lottery Ticket Hypothesis: Pruning is All You Need》
No 18. 《Latent space visualization, characterization, and generation of diverse vocal communication signals》
No 19. 《Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals》
No 20. 《Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization》
No 21. 《ABCTracker: an easy-to-use, cloud-based application for tracking multiple objects》
No 22. 《Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization》
No 23. 《Rapid Adaptation of BERT for Information Extraction on Domain-Specific Business Documents》
No 24. 《Towards Open-Set Semantic Segmentation of Aerial Images》
No 25. 《Depth Based Semantic Scene Completion with Position Importance Aware Loss》
No 26. 《Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus》
No 27. 《Uncertainty Quantification for Bayesian Optimization》
No 28. 《Probabilistic 3D Multi-Object Tracking for Autonomous Driving》
No 29. 《Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos》
No 30. 《Community Detection in Bipartite Networks with Stochastic Blockmodels》

No 1. 《A Simple Framework for Contrastive Learning of Visual Representations》
No 2. 《Image-to-Image Translation with Text Guidance》
No 3. 《A review on outlier/anomaly detection in time series data》
No 4. 《Unsupervised Discovery of Interpretable Directions in the GAN Latent Space》
No 5. 《Supervised Learning on Relational Databases with Graph Neural Networks》
No 6. 《REALM: Retrieval-Augmented Language Model Pre-Training》
No 7. 《Image Fine-grained Inpainting》
No 8. 《Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving》
No 9. 《Aligning the Pretraining and Finetuning Objectives of Language Models》
No 10. 《Improving the Robustness of Graphs through Reinforcement Learning and Graph Neural Networks》
No 11. 《Subspace Capsule Network》
No 12. 《Deep Graph Mapper: Seeing Graphs through the Neural Lens》
No 13. 《fastai: A Layered API for Deep Learning》
No 14. 《Adversarial Training for Aspect-Based Sentiment Analysis with BERT》
No 15. 《Self-training with Noisy Student improves ImageNet classification》
No 16. 《Exponential Step Sizes for Non-Convex Optimization》
No 17. 《Attentive Group Equivariant Convolutional Networks》
No 18. 《Self-Distillation Amplifies Regularization in Hilbert Space》
No 19. 《Joint Deep Learning of Facial Expression Synthesis and Recognition》
No 20. 《The Bloom Tree》
No 21. 《WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale》
No 22. 《A Probabilistic Formulation of Unsupervised Text Style Transfer》
No 23. 《Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights》
No 24. 《Causally Correct Partial Models for Reinforcement Learning》
No 25. 《Time Series Alignment with Global Invariances》
No 26. 《Weakly-Supervised Disentanglement Without Compromises》
No 27. 《DeepBrain: Towards Personalized EEG Interaction through Attentional and Embedded LSTM Learning》
No 28. 《Unbalanced GANs: Pre-training the Generator of Generative Adversarial Network using Variational Autoencoder》
No 29. 《Non-linear regression models for behavioral and neural data analysis》
No 30. 《Blank Language Models》

No 1. 《Deep Learning for Financial Applications : A Survey》
No 2. 《Tree-SNE: Hierarchical Clustering and Visualization Using t-SNE》
No 3. 《Image-to-Image Translation with Text Guidance》
No 4. 《A Simple Framework for Contrastive Learning of Visual Representations》
No 5. 《Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? -- A Neural Tangent Kernel Perspective》
No 6. 《HGAT: Hierarchical Graph Attention Network for Fake News Detection》
No 7. 《Bayesian Deep Learning and a Probabilistic Perspective of Generalization》
No 8. 《Geom-GCN: Geometric Graph Convolutional Networks》
No 9. 《BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning》
No 10. 《LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation》
No 11. 《Decision-Making with Auto-Encoding Variational Bayes》
No 12. 《Transformers as Soft Reasoners over Language》
No 13. 《Deep learning of dynamical attractors from time series measurements》
No 14. 《Holes in Bayesian Statistics》
No 15. 《Neural Approaches to Conversational AI》
No 16. 《Exponential Step Sizes for Non-Convex Optimization》
No 17. 《Self-Distillation Amplifies Regularization in Hilbert Space》
No 18. 《Disease State Prediction From Single-Cell Data Using Graph Attention Networks》
No 19. 《Transformer on a Diet》
No 20. 《Variational Autoencoders with Riemannian Brownian Motion Priors》
No 21. 《Self-Supervised Linear Motion Deblurring》
No 22. 《Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping》
No 23. 《Capsules with Inverted Dot-Product Attention Routing》
No 24. 《Kalman meets Bellman: Improving Policy Evaluation through Value Tracking》
No 25. 《The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence》
No 26. 《Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior》
No 27. 《Do We Need Zero Training Loss After Achieving Zero Training Error?》
No 28. 《Graph Similarity Using PageRank and Persistent Homology》
No 29. 《Self-supervised learning for audio-visual speaker diarization》
No 30. 《Speech-to-Singing Conversion in an Encoder-Decoder Framework》

No 1. 《Rethinking Bias-Variance Trade-off for Generalization of Neural Networks》
No 2. 《Generalization and Representational Limits of Graph Neural Networks》
No 3. 《Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks》
No 4. 《How Much Knowledge Can You Pack Into the Parameters of a Language Model?》
No 5. 《CausalML: Python Package for Causal Machine Learning》
No 6. 《Bayesian Deep Learning and a Probabilistic Perspective of Generalization》
No 7. 《A Primer in BERTology: What we know about how BERT works》
No 8. 《MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers》
No 9. 《t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections》
No 10. 《Multivariate time-series modeling with generative neural networks》
No 11. 《Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning》
No 12. 《Joint Embedding in Named Entity Linking on Sentence Level》
No 13. 《Fast Differentiable Sorting and Ranking》
No 14. 《Affinity and Diversity: Quantifying Mechanisms of Data Augmentation》
No 15. 《Gradient Boosting Neural Networks: GrowNet》
No 16. 《Bayesian Computing in the Statistics and Data Science Curriculum》
No 17. 《PolyGen: An Autoregressive Generative Model of 3D Meshes》
No 18. 《T-Net: A Template-Supervised Network for Task-specific Feature Extraction in Biomedical Image Analysis》
No 19. 《Few-shot Natural Language Generation for Task-Oriented Dialog》
No 20. 《Freeze Discriminator: A Simple Baseline for Fine-tuning GANs》
No 21. 《Batch Normalization Biases Deep Residual Networks Towards Shallow Paths》
No 22. 《Neural Network Compression Framework for fast model inference》
No 23. 《Adversarial Machine Learning -- Industry Perspectives》
No 24. 《Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-Layer Networks》
No 25. 《Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent》
No 26. 《BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images》
No 27. 《Do We Need Zero Training Loss After Achieving Zero Training Error?》
No 28. 《Human-centered Explainable AI: Towards a Reflective Sociotechnical Approach》
No 29. 《Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image》
No 30. 《A Hierarchy of Limitations in Machine Learning》

No 1. 《Time Series Data Augmentation for Deep Learning: A Survey》
No 2. 《Memory-Based Graph Networks》
No 3. 《Data Augmentation using Pre-trained Transformer Models》
No 4. 《Natural Language Processing Advancements By Deep Learning: A Survey》
No 5. 《Knowledge Graphs on the Web -- an Overview》
No 6. 《Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs》
No 7. 《Benchmarking Graph Neural Networks》
No 8. 《BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward》
No 9. 《Creating High Resolution Images with a Latent Adversarial Generator》
No 10. 《The Two Regimes of Deep Network Training》
No 11. 《Predicting Neural Network Accuracy from Weights》
No 12. 《Understanding and Mitigating the Tradeoff Between Robustness and Accuracy》
No 13. 《Deep Image Spatial Transformation for Person Image Generation》
No 14. 《The Early Phase of Neural Network Training》
No 15. 《Probabilistic Learning on Manifolds》
No 16. 《Representation Learning Through Latent Canonicalizations》
No 17. 《Statistical power for cluster analysis》
No 18. 《A U-Net Based Discriminator for Generative Adversarial Networks》
No 19. 《Image Matching across Wide Baselines: From Paper to Practice》
No 20. 《RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks》
No 21. 《Is the Meta-Learning Idea Able to Improve the Generalization of Deep Neural Networks on the Standard Supervised Learning?》
No 22. 《Policy Evaluation Networks》
No 23. 《Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study》
No 24. 《Sketch-to-Art: Synthesizing Stylized Art Images From Sketches》
No 25. 《Theoretical Models of Learning to Learn》
No 26. 《D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry》
No 27. 《Causal Inference With Selectively-Deconfounded Data》
No 28. 《Semi-Supervised Speech Recognition via Local Prior Matching》
No 29. 《Image Generation from Freehand Scene Sketches》
No 30. 《CookGAN: Meal Image Synthesis from Ingredients》

No 1. 《A Survey on The Expressive Power of Graph Neural Networks》
No 2. 《Deep Learning for Financial Applications : A Survey》
No 3. 【基于图网络的复杂物理3D仿真】
No 4. 《Natural Language Processing Advancements By Deep Learning: A Survey》
No 5. 《Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation》
No 6. 《Imbalance Problems in Object Detection: A Review》
No 7. 《Lung Infection Quantification of COVID-19 in CT Images with Deep Learning》
No 8. 《AutoML-Zero: Evolving Machine Learning Algorithms From Scratch》
No 9. 《Creating High Resolution Images with a Latent Adversarial Generator》
No 10. 《BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward》
No 11. 《Meta-Transfer Learning for Zero-Shot Super-Resolution》
No 12. 《Hyper-Parameter Optimization: A Review of Algorithms and Applications》
No 13. 《Semi-Supervised StyleGAN for Disentanglement Learning》
No 14. 《Semi-supervised Anomaly Detection on Attributed Graphs》
No 15. 《Learning to be Global Optimizer》
No 16. 《What is the State of Neural Network Pruning?》
No 17. 《Pop Music Transformer: Generating Music with Rhythm and Harmony》
No 18. 《Learning in the Frequency Domain》
No 19. 《Deep Learning in Mining Biological Data》
No 20. 《Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective》
No 21. 《When Deep Learning Meets Data Alignment: A Review on Deep Registration Networks (DRNs)》
No 22. 《Improved Baselines with Momentum Contrastive Learning》
No 23. 《TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing》
No 24. 《What the [MASK]? Making Sense of Language-Specific BERT Models》
No 25. 《StyleGAN2 Distillation for Feed-forward Image Manipulation》
No 26. 《Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation》
No 27. 《Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning》
No 28. 《Image Generation from Freehand Scene Sketches》
No 29. 《Advanced kNN: A Mature Machine Learning Series》
No 30. 《When are Bayesian model probabilities overconfident?》

No 1. 《Stanza: A Python Natural Language Processing Toolkit for Many Human Languages》
No 2. 《Pre-trained Models for Natural Language Processing: A Survey》
No 3. 《Hyper-Parameter Optimization: A Review of Algorithms and Applications》
No 4. 《Rethinking Batch Normalization in Transformers》
No 5. 《Convolutional Kernel Networks for Graph-Structured Data》
No 6. 《A New Meta-Baseline for Few-Shot Learning》
No 7. 《AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data》
No 8. 《What Information Does a ResNet Compress?》
No 9. 《Extended Batch Normalization》
No 10. 《TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding》
No 11. 《Sampling on Graphs: From Theory to Applications》
No 12. 《Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking》
No 13. 《OpenGAN: Open Set Generative Adversarial Networks》
No 14. 《Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images》
No 15. 《The twitter explorer: a framework for observing Twitter through interactive networks》
No 16. 《Ford Multi-AV Seasonal Dataset》
No 17. 《KGvec2go -- Knowledge Graph Embeddings as a Service》
No 18. 《Tracking COVID-19 using online search》
No 19. 《Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective》
No 20. 《Semantic Pyramid for Image Generation》
No 21. 《Synthesizing human-like sketches from natural images using a conditional convolutional decoder》
No 22. 《Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks》
No 23. 《A Survey of End-to-End Driving: Architectures and Training Methods》
No 24. 《Self-supervised Single-view 3D Reconstruction via Semantic Consistency》
No 25. 《Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems》
No 26. 《Equalization Loss for Long-Tailed Object Recognition》
No 27. 《On the Convergence of Adam and Adagrad》
No 28. 《SDVTracker: Real-Time Multi-Sensor Association and Tracking for Self-Driving Vehicles》
No 29. 《Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling》
No 30. 《Blur, Noise, and Compression Robust Generative Adversarial Networks》

No 1. 《A Survey on Contextual Embeddings》
No 2. 《Metric learning: cross-entropy vs. pairwise losses》
No 3. 《Meta Pseudo Labels》
No 4. 《SOLOv2: Dynamic, Faster and Stronger》
No 5. 《Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?》
No 6. 《Do CNNs Encode Data Augmentations?》
No 7. 《ProGraML: Graph-based Deep Learning for Program Optimization and Analysis》
No 8. 《TF-IDFC-RF: A Novel Supervised Term Weighting Scheme》
No 9. 《ASLFeat: Learning Local Features of Accurate Shape and Localization》
No 10. 《A Survey of Methods for Low-Power Deep Learning and Computer Vision》
No 11. 《COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images》
No 12. 《Pre-trained Models for Natural Language Processing: A Survey》
No 13. 《An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation》
No 14. 《Atlas: End-to-End 3D Scene Reconstruction from Posed Images》
No 15. 《Deformable Style Transfer》
No 16. 《End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds》
No 17. 《High Accuracy Face Geometry Capture using a Smartphone Video》
No 18. 《CPS: Class-level 6D Pose and Shape Estimation From Monocular Images》
No 19. 《GAN Compression: Efficient Architectures for Interactive Conditional GANs》
No 20. 《Collaborative Distillation for Ultra-Resolution Universal Style Transfer》
No 21. 《Deep Line Art Video Colorization with a Few References》
No 22. 《Fixing the train-test resolution discrepancy: FixEfficientNet》
No 23. 《Weighted Meta-Learning》
No 24. 《Neural Networks are Surprisingly Modular》
No 25. 《Calibration of Pre-trained Transformers》
No 26. 《MINT: Deep Network Compression via Mutual Information-based Neuron Trimming》
No 27. 《Overinterpretation reveals image classification model pathologies》
No 28. 《High-Resolution Daytime Translation Without Domain Labels》
No 29. 《Neural Contours: Learning to Draw Lines from 3D Shapes》
No 30. 《Self-Supervised Contextual Bandits in Computer Vision》

No 1. 《word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data》
No 2. 《Suphx: Mastering Mahjong with Deep Reinforcement Learning》
No 3. 《COVID-CT-Dataset: A CT Scan Dataset about COVID-19》
No 4. 《Multi-Label Text Classification using Attention-based Graph Neural Network》
No 5. 《Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks》
No 6. 《How Useful is Self-Supervised Pretraining for Visual Tasks?》
No 7. 《CNN-based Density Estimation and Crowd Counting: A Survey》
No 8. 《Watching the World Go By: Representation Learning from Unlabeled Videos》
No 9. 《Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations》
No 10. 《Scene Text Recognition via Transformer》
No 11. 《Word2Vec: Optimal Hyper-Parameters and Their Impact on NLP Downstream Tasks》
No 12. 《Difference Attention Based Error Correction LSTM Model for Time Series Prediction》
No 13. 《A Survey of Deep Learning for Scientific Discovery》
No 14. 《Author2Vec: A Framework for Generating User Embedding》
No 15. 《Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection》
No 16. 《Data Science in Economics》
No 17. 《Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers》
No 18. 《Controllable Person Image Synthesis with Attribute-Decomposed GAN》
No 19. 《Causal Inference with Spatio-temporal Data: Estimating the Effects of Airstrikes on Insurgent Violence in Iraq》
No 20. 《Statistical Queries and Statistical Algorithms: Foundations and Applications》
No 21. 《Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images》
No 22. 《Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification》
No 23. 《Lightweight Photometric Stereo for Facial Details Recovery》
No 24. 《Learning to Correct Overexposed and Underexposed Photos》
No 25. 《COVID-19 Image Data Collection》
No 26. 《Beyond the Ground-Truth: An Evaluator-Generator Framework for Group-wise Learning-to-Rank in E-Commerce》
No 27. 《Are Labels Necessary for Neural Architecture Search?》
No 28. 《Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation》
No 29. 《PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization》
No 30. 《Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision》

No 1. 【老照片也能玩3D:上下文感知三维图像分层深度修复技术】
No 2. 《Deep Learning Based Text Classification: A Comprehensive Review》
No 3. 《Learning to See Through Obstructions》
No 4. 《Bridging the gap between graphs and networks》
No 5. 《Tracking Objects as Points》
No 6. 《Background Matting: The World is Your Green Screen》
No 7. 《Faster Gaussian Processes via Deep Embeddings》
No 8. 《Financial Time Series Representation Learning》
No 9. 《One-Shot Domain Adaptation For Face Generation》
No 10. 《Generalized Zero-Shot Learning Via Over-Complete Distribution》
No 11. 《Semi-supervised Learning for Few-shot Image-to-Image Translation》
No 12. 《Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence》
No 13. 《RANSAC-Flow: generic two-stage image alignment》
No 14. 《Feature Quantization Improves GAN Training》
No 15. 《Learning Representations For Images With Hierarchical Labels》
No 16. 《FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction》
No 17. 《Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy》
No 18. 《Evolving Normalization-Activation Layers》
No 19. 《Attentive Normalization for Conditional Image Generation》
No 20. 《Suphx: Mastering Mahjong with Deep Reinforcement Learning》
No 21. 《Meta-learning curiosity algorithms》
No 22. 《Weakly Supervised Dataset Collection for Robust Person Detection》
No 23. 《In-Domain GAN Inversion for Real Image Editing》
No 24. 《A County-level Dataset for Informing the United States' Response to COVID-19》
No 25. 《Improving 3D Object Detection through Progressive Population Based Augmentation》
No 26. 《Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence》
No 27. 《Self-Supervised Scene De-occlusion》
No 28. 《MetNet: A Neural Weather Model for Precipitation Forecasting》
No 29. 《Adversarial Latent Autoencoders》
No 30. 《GANSpace: Discovering Interpretable GAN Controls》

No 1. 《Meta-Learning in Neural Networks: A Survey》
No 2. 《MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices》
No 3. 【老照片也能玩3D:上下文感知三维图像分层深度修复技术】
No 4. 《Longformer: The Long-Document Transformer》
No 5. 《3D IoU-Net: IoU Guided 3D Object Detector for Point Clouds》
No 6. 《Spatially Attentive Output Layer for Image Classification》
No 7. 《Boosting Semantic Human Matting with Coarse Annotations》
No 8. 《Unsupervised Domain Clusters in Pretrained Language Models》
No 9. 《k-Nearest Neighbour Classifiers -- 2nd Edition》
No 10. 《PALM: Pre-training an Autoencoding&Autoregressive Language Model for Context-conditioned Generation》
No 11. 《Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision》
No 12. 《Deep Manifold Prior》
No 13. 《Poor Man's BERT: Smaller and Faster Transformer Models》
No 14. 《When Does Unsupervised Machine Translation Work?》
No 15. 《Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images》
No 16. 《Feedback Recurrent Autoencoder for Video Compression》
No 17. 《Self6D: Self-Supervised Monocular 6D Object Pose Estimation》
No 18. 《Continual Reinforcement Learning with Multi-Timescale Replay》
No 19. 《AI Feynman: a Physics-Inspired Method for Symbolic Regression》
No 20. 《Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19》
No 21. 《Tensor Decompositions for temporal knowledge base completion》
No 22. 《Geometry-Aware Gradient Algorithms for Neural Architecture Search》
No 23. 《QuantNet: Transferring Learning Across Systematic Trading Strategies》
No 24. 《KFNet: Learning Temporal Camera Relocalization using Kalman Filtering》
No 25. 《Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning》
No 26. 《Managing Diversity in Airbnb Search》
No 27. 《FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding》
No 28. 《Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems》
No 29. 《Weight Poisoning Attacks on Pre-trained Models》
No 30. 《An In-depth Walkthrough on Evolution of Neural Machine Translation》

No 1. 《k-Nearest Neighbour Classifiers -- 2nd Edition》
No 2. 《AI Feynman: a Physics-Inspired Method for Symbolic Regression》
No 3. 《The GeoLifeCLEF 2020 Dataset》
No 4. 《Unpaired Photo-to-manga Translation Based on The Methodology of Manga Drawing》
No 5. 【从头训练个NLP模型要花多少钱?用非抢占AWS/GCP实例不打折的话,依模型大小,差不多要5万到1千万美元】
No 6. 《Clustering Time Series Data through Autoencoder-based Deep Learning Models》
No 7. 《Bringing Old Photos Back to Life》
No 8. 《A Comprehensive Overview and Survey of Recent Advances in Meta-Learning》
No 9. 《ResNeSt: Split-Attention Networks》
No 10. 《Spatially Attentive Output Layer for Image Classification》
No 11. 《Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision》
No 12. 《Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance》
No 13. 《Representation Learning of Histopathology Images using Graph Neural Networks》
No 14. 【新药发现最新进展:基于对抗自编码器的所需转录组特定变化分子生成,可推断用于诱导基因期望表达变化的药物分子】
No 15. 《Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model》
No 16. 《Efficient Neighbourhood Consensus Networks via Submanifold Sparse Convolutions》
No 17. 《Vector Quantized Contrastive Predictive Coding for Template-based Music Generation》
No 18. 《Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization》
No 19. 《SpaceNet 6: Multi-Sensor All Weather Mapping Dataset》
No 20. 《Machine learning for causal inference: on the use of cross-fit estimators》
No 21. 《Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction》
No 22. 《PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks》
No 23. 《A Review on Deep Learning Techniques for Video Prediction》
No 24. 《Controllable Variational Autoencoder》
No 25. 《Layered Graph Embedding for Entity Recommendation using Wikipedia in the Yahoo! Knowledge Graph》
No 26. 《Community detection with node attributes in multilayer networks》
No 27. 《A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric Approaches》
No 28. 《Document-level Representation Learning using Citation-informed Transformers》
No 29. 《Learning Over Dirty Data Without Cleaning》
No 30. 《Continual Reinforcement Learning with Multi-Timescale Replay》

No 1. 《Learning-to-Rank with BERT in TF-Ranking》
No 2. 【让人人都变得“彬彬有礼”:礼貌迁移任务——在保留意义的同时将非礼貌语句转换为礼貌语句,提供包含1.39M + 实例的数据集】
No 3. 《TLDR: Extreme Summarization of Scientific Documents》
No 4. 《Lite Transformer with Long-Short Range Attention》
No 5. 《Attention Module is Not Only a Weight: Analyzing Transformers with Vector Norms》
No 6. 《ToTTo: A Controlled Table-To-Text Generation Dataset》
No 7. 《Light-Weighted CNN for Text Classification》
No 8. 《Named Entity Recognition without Labelled Data: A Weak Supervision Approach》
No 9. 《Pyramid Attention Networks for Image Restoration》
No 10. 《CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization》
No 11. 【ByteSing:效果逼真的中文歌唱合成系统】
No 12. 《Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels》
No 13. 《NAIST COVID: Multilingual COVID-19 Twitter and Weibo Dataset》
No 14. 《CoronaVis: A Real-time COVID-19 Tweets Analyzer》
No 15. 《VGGSound: A Large-scale Audio-Visual Dataset》
No 16. 《Reinforcement Learning with Augmented Data》
No 17. 《Neural Additive Models: Interpretable Machine Learning with Neural Nets》
No 18. 《Knowledge Graph Embeddings and Explainable AI》
No 19. 《Why should we add early exits to neural networks?》
No 20. 《Decoupling Global and Local Representations from/for Image Generation》
No 21. 《Improved Residual Networks for Image and Video Recognition》
No 22. 《Deep Learning for Screening COVID-19 using Chest X-Ray Images》
No 23. 《One-Shot Identity-Preserving Portrait Reenactment》
No 24. 《The Creation and Detection of Deepfakes: A Survey》
No 25. 《DGL-KE: Training Knowledge Graph Embeddings at Scale》
No 26. 《Explainable Deep Learning: A Field Guide for the Uninitiated》
No 27. 《SIGN: Scalable Inception Graph Neural Networks》
No 28. 《DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference》
No 29. 《On the Synergies between Machine Learning and Stereo: a Survey》
No 30. 《Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoder》

No 1. 《A survey on domain adaptation theory》
No 2. 《Synthesizer: Rethinking Self-Attention in Transformer Models》
No 3. 《Zero-shot Entity Linking with Dense Entity Retrieval》
No 4. 《Improving Semantic Segmentation via Self-Training》
No 5. 《Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction》
No 6. 《LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands and Water from Aerial Imagery》
No 7. 《Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense》
No 8. 《When does data augmentation help generalization in NLP?》
No 9. 《Deep Divergence Learning》
No 10. 《Cross-domain Correspondence Learning for Exemplar-based Image Translation》
No 11. 《Collective Loss Function for Positive and Unlabeled Learning》
No 12. 《Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems》
No 13. 《Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?》
No 14. 《Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks》
No 15. 《Open Graph Benchmark: Datasets for Machine Learning on Graphs》
No 16. 《Deep 3D Portrait from a Single Image》
No 17. 《Investigating Transferability in Pretrained Language Models》
No 18. 《DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering》
No 19. 《Correlating Edge, Pose with Parsing》
No 20. 《Learning Feature Descriptors using Camera Pose Supervision》
No 21. 《Learning to Forecast and Forecasting to Learn from the COVID-19 Pandemic》
No 22. 《A simulation study of disaggregation regression for spatial disease mapping》
No 23. 《Adversarial Synthesis of Human Pose from Text》
No 24. 《Learning to Autofocus》
No 25. 《Self-Supervised Human Depth Estimation from Monocular Videos》
No 26. 《A Large Dataset of Historical Japanese Documents with Complex Layouts》
No 27. 《Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations》
No 28. 《POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS)》
No 29. 《Low-Dimensional Hyperbolic Knowledge Graph Embeddings》
No 30. 《Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels》

No 1. 《Machine Learning on Graphs: A Model and Comprehensive Taxonomy》
No 2. 《Unsupervised Anomaly Detection via Deep Metric Learning with End-to-End Optimization》
No 3. 《Explainable Reinforcement Learning: A Survey》
No 4. 《Improving Semantic Segmentation via Self-Training》
No 5. 《DeepFaceLab: A simple, flexible and extensible face swapping framework》
No 6. 《Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding》
No 7. 《Monte Carlo Geometry Processing: A Grid-Free Approach to PDE-Based Methods on Volumetric Domains》
No 8. 《Collective Loss Function for Positive and Unlabeled Learning》
No 9. 《The Cascade Transformer: an Application for Efficient Answer Sentence Selection》
No 10. 《The Information Bottleneck Problem and Its Applications in Machine Learning》
No 11. 《Wavelet Integrated CNNs for Noise-Robust Image Classification》
No 12. 《SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving》
No 13. 《Geometric graphs from data to aid classification tasks with graph convolutional networks》
No 14. 《Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis》
No 15. 《DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses》
No 16. 《A Causal View on Robustness of Neural Networks》
No 17. 《Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions》
No 18. 《Toward Better Storylines with Sentence-Level Language Models》
No 19. 《A simulation study of disaggregation regression for spatial disease mapping》
No 20. 《Local Self-Attention over Long Text for Efficient Document Retrieval》
No 21. 《HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning》
No 22. 《FroDO: From Detections to 3D Objects》
No 23. 《Self-Supervised Human Depth Estimation from Monocular Videos》
No 24. 《Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning?》
No 25. 《RigNet: Neural Rigging for Articulated Characters》
No 26. 《Enabling Language Models to Fill in the Blanks》
No 27. 《FaR-GAN for One-Shot Face Reenactment》
No 28. 《ExpBERT: Representation Engineering with Natural Language Explanations》
No 29. 《Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors》
No 30. 《SciREX: A Challenge Dataset for Document-Level Information Extraction》

No 1. 《What makes for good views for contrastive learning》
No 2. 《Why distillation helps: a statistical perspective》
No 3. 《COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter》
No 4. 《An Overview of Privacy in Machine Learning》
No 5. 《FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval》
No 6. 《Review of Text Style Transfer Based on Deep Learning》
No 7. 《Contextual Embeddings: When Are They Worth It?》
No 8. 《Map Generation from Large Scale Incomplete and Inaccurate Data Labels》
No 9. 《Combining detection and tracking for human pose estimation in videos》
No 10. 《Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere》
No 11. 《Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement》
No 12. 《Towards Robustifying NLI Models Against Lexical Dataset Biases》
No 13. 《Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors》
No 14. 《Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box》
No 15. 《S2IGAN: Speech-to-Image Generation via Adversarial Learning》
No 16. 《DeepFaceFlow: In-the-wild Dense 3D Facial Motion Estimation》
No 17. 《An LSTM approach to Predict Migration based on Google Trends》
No 18. 《Prototypical Contrastive Learning of Unsupervised Representations》
No 19. 《Making Robots Draw A Vivid Portrait In Two Minutes》
No 20. 《TextAttack: A Framework for Adversarial Attacks in Natural Language Processing》
No 21. 《BERTweet: A pre-trained language model for English Tweets》
No 22. 《Epipolar Transformers》
No 23. 《Bayesian Bits: Unifying Quantization and Pruning》
No 24. 《Learning Rate Annealing Can Provably Help Generalization, Even for Convex Problems》
No 25. 《Portrait Shadow Manipulation》
No 26. 《Neutral Bots Reveal Political Bias on Social Media》
No 27. 《BIOMRC: A Dataset for Biomedical Machine Reading Comprehension》
No 28. 《FaceFilter: Audio-visual speech separation using still images》
No 29. 《Bi3D: Stereo Depth Estimation via Binary Classifications》
No 30. 《Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization》

No 1. 《Why distillation helps: a statistical perspective》
No 2. 《End-to-End Object Detection with Transformers》
No 3. 《Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3》
No 4. 《The best way to select features?》
No 5. 《3D Augmented Reality-Assisted CT-Guided Interventions: System Design and Preclinical Trial on an Abdominal Phantom using HoloLens 2》
No 6. 《Learning To Classify Images Without Labels》
No 7. 《Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks》
No 8. 《Attention-based network for low-light image enhancement》
No 9. 《Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models》
No 10. 《Point2Mesh: A Self-Prior for Deformable Meshes》
No 11. 《High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling》
No 12. 《An Adversarial Approach for Explaining the Predictions of Deep Neural Networks》
No 13. 《Is deeper better? It depends on locality of relevant features》
No 14. 《MMFashion: An Open-Source Toolbox for Visual Fashion Analysis》
No 15. 《Wish You Were Here: Context-Aware Human Generation》
No 16. 《Instance-aware Image Colorization》
No 17. 《Generative Adversarial Networks for photo to Hayao Miyazaki style cartoons》
No 18. 《Kernel methods library for pattern analysis and machine learning in python》
No 19. 《End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection》
No 20. 《Manifold Alignment for Semantically Aligned Style Transfer》
No 21. 《Model-Based Robust Deep Learning》
No 22. 《Domain Conditioned Adaptation Network》
No 23. 《SegAttnGAN: Text to Image Generation with Segmentation Attention》
No 24. 《Efficient Pig Counting in Crowds with Keypoints Tracking and Spatial-aware Temporal Response Filtering》
No 25. 《Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks》
No 26. 《Statistical Analysis of Data Repeatability Measures》
No 27. 《TAO: A Large-Scale Benchmark for Tracking Any Object》
No 28. 《Feature Purification: How Adversarial Training Performs Robust Deep Learning》
No 29. 《GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information》
No 30. 《TIME: Text and Image Mutual-Translation Adversarial Networks》

No 1. 《Extracting COVID-19 Events from Twitter》
No 2. 【Penrose:根据数学公式自动绘图】
No 3. 《Bayesian Neural Networks》
No 4. 《Language Models are Few-Shot Learners》
No 5. 《Cascaded Text Generation with Markov Transformers》
No 6. 《Rethinking Assumptions in Deep Anomaly Detection》
No 7. 《SurfaceNet+: An End-to-end 3D Neural Network for Very Sparse Multi-view Stereopsis》
No 8. 《Machine learning in spectral domain》
No 9. 《Explainable Artificial Intelligence: a Systematic Review》
No 10. 《Deep Generation of Face Images from Sketches》
No 11. 《DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution》
No 12. 《Ridge Regularizaton: an Essential Concept in Data Science》
No 13. 《Ultrasound Video Summarization using Deep Reinforcement Learning》
No 14. 《Syntactic Structure Distillation Pretraining For Bidirectional Encoders》
No 15. 《Complex networks for event detection in heterogeneous high volume news streams》
No 16. 《Reducing BERT Pre-Training Time from 3 Days to 76 Minutes》
No 17. 《Recapture as You Want》
No 18. 《Adversarial Attacks and Defense on Textual Data: A Review》
No 19. 《Some Theoretical Insights into Wasserstein GANs》
No 20. 《From ImageNet to Image Classification: Contextualizing Progress on Benchmarks》
No 21. 《Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining》
No 22. 《Foreground-aware Semantic Representations for Image Harmonization》
No 23. 《exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformers Models》
No 24. 《Ordinal Non-negative Matrix Factorization for Recommendation》
No 25. 《CNNs on Surfaces using Rotation-Equivariant Features》
No 26. 《Reference Guided Face Component Editing》
No 27. 《Reinforcement learning with human advice. A survey》
No 28. 《Networks beyond pairwise interactions: structure and dynamics》
No 29. 《Motion2Vec: Semi-Supervised Representation Learning from Surgical Videos》
No 30. 《Predicting Goal-directed Human Attention Using Inverse Reinforcement Learning》

No 1. 《Pointer Graph Networks》
No 2. 《Anomaly Detection with Tensor Networks》
No 3. 【阿里家的GPU】
No 4. 《Similarity-based Classification: Connecting Similarity Learning to Binary Classification》
No 5. 《XGNN: Towards Model-Level Explanations of Graph Neural Networks》
No 6. 《A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions》
No 7. 《An Overview of Neural Network Compression》
No 8. 《Linformer: Self-Attention with Linear Complexity》
No 9. 《All Local Minima are Global for Two-Layer ReLU Neural Networks: The Hidden Convex Optimization Landscape》
No 10. 《Deep Stock Predictions》
No 11. 《A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning》
No 12. 《Deep Structural Causal Models for Tractable Counterfactual Inference》
No 13. 《You say Normalizing Flows I see Bayesian Networks》
No 14. 《Rethinking the Truly Unsupervised Image-to-Image Translation》
No 15. 《Implicit Kernel Attention》
No 16. 《CoCon: A Self-Supervised Approach for Controlled Text Generation》
No 17. 《Unsupervised Translation of Programming Languages》
No 18. 《Learning to Detect 3D Objects from Point Clouds in Real Time》
No 19. 《Artificial neural networks for neuroscientists: A primer》
No 20. 《Big GANs Are Watching You: Towards Unsupervised Object Segmentation with Off-the-Shelf Generative Models》
No 21. 《Variational Auto-Regressive Gaussian Processes for Continual Learning》
No 22. 《Revisiting Few-sample BERT Fine-tuning》
No 23. 《The Lipschitz Constant of Self-Attention》
No 24. 《Neural Architecture Search without Training》
No 25. 《BERT Loses Patience: Fast and Robust Inference with Early Exit》
No 26. 《Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties》
No 27. 《A mathematical model for automatic differentiation in machine learning》
No 28. 《Adversarial Feature Desensitization》
No 29. 《Evaluating the Disentanglement of Deep Generative Models through Manifold Topology》
No 30. 《Super-resolution Variational Auto-Encoders》

No 1. 【具有周期激活函数的隐式神经网络表示】
No 2. 《An Algorithmic Introduction to Clustering》
No 3. 《What Do Neural Networks Learn When Trained With Random Labels?》
No 4. 《Rethinking Pre-training and Self-training》
No 5. 《Deep Stock Predictions》
No 6. 《Anomaly Detection with Domain Adaptation》
No 7. 《A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions》
No 8. 《Self-Supervised Relational Reasoning for Representation Learning》
No 9. 《Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies》
No 10. 《Training Generative Adversarial Networks with Limited Data》
No 11. 《All Local Minima are Global for Two-Layer ReLU Neural Networks: The Hidden Convex Optimization Landscape》
No 12. 《Self-supervised Learning on Graphs: Deep Insights and New Direction》
No 13. 《Noise or Signal: The Role of Image Backgrounds in Object Recognition》
No 14. 《Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild》
No 15. 《Big Self-Supervised Models are Strong Semi-Supervised Learners》
No 16. 《Disentangled Non-Local Neural Networks》
No 17. 《Is deep learning necessary for simple classification tasks?》
No 18. 《Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective》
No 19. 《Sparse and Continuous Attention Mechanisms》
No 20. 《Super-resolution Variational Auto-Encoders》
No 21. 《Temporal Graph Networks for Deep Learning on Dynamic Graphs》
No 22. 《Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks》
No 23. 《Variational Auto-Regressive Gaussian Processes for Continual Learning》
No 24. 《Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning》
No 25. 《LSD-C: Linearly Separable Deep Clusters》
No 26. 《Monte Carlo Gradient Estimation in Machine Learning》
No 27. 【PULSE:生成模型潜空间探索自监督照片上采样(用降采样损失训练超分辨率模型)】
No 28. 《Wavelet Networks: Scale Equivariant Learning From Raw Waveforms》
No 29. 《An overall view of key problems in algorithmic trading and recent progress》
No 30. 《Why Normalizing Flows Fail to Detect Out-of-Distribution Data》

No 1. 《What Do Neural Networks Learn When Trained With Random Labels?》
No 2. 《Graph Meta Learning via Local Subgraphs》
No 3. 《A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence》
No 4. 《Rethinking Semi-Supervised Learning in VAEs》
No 5. 《UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders》
No 6. 《Cross-domain Correspondence Learning for Exemplar-based Image Translation》
No 7. 《Detection in Crowded Scenes: One Proposal, Multiple Predictions》
No 8. 《Zero-Shot Learning with Common Sense Knowledge Graphs》
No 9. 《A Tutorial on VAEs: From Bayes' Rule to Lossless Compression》
No 10. 《Self-supervised Learning on Graphs: Deep Insights and New Direction》
No 11. 《Online Deep Clustering for Unsupervised Representation Learning》
No 12. 《Self-supervised Video Object Segmentation》
No 13. 《Attention Mesh: High-fidelity Face Mesh Prediction in Real-time》
No 14. 《Deep Learning Based Text Classification: A Comprehensive Review》
No 15. 《When Do Neural Networks Outperform Kernel Methods?》
No 16. 《wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations》
No 17. 《Contrastive Generative Adversarial Networks》
No 18. 《To Pretrain or Not to Pretrain: Examining the Benefits of Pretraining on Resource Rich Tasks》
No 19. 《A generalized Bayes framework for probabilistic clustering》
No 20. 《Graph Neural Networks in TensorFlow and Keras with Spektral》
No 21. 《Model-based Adversarial Meta-Reinforcement Learning》
No 22. 《Temporal Graph Networks for Deep Learning on Dynamic Graphs》
No 23. 【PULSE:生成模型潜空间探索自监督照片上采样(用降采样损失训练超分辨率模型)】
No 24. 《Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample》
No 25. 《CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks》
No 26. 《Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting》
No 27. 《Depth Uncertainty in Neural Networks》
No 28. 《Latent Video Transformer》
No 29. 《ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping》
No 30. 《Learning Invariant Representations for Reinforcement Learning without Reconstruction》

No 1. 《Graph Structured Network for Image-Text Matching》
No 2. 【博士论文:自然语言深度潜变量模型】
No 3. 《Multi-Head Attention: Collaborate Instead of Concatenate》
No 4. 《PyTorch Distributed: Experiences on Accelerating Data Parallel Training》
No 5. 《APQ: Joint Search for Nerwork Architecture, Pruning and Quantization Policy》
No 6. 《Model-based Reinforcement Learning: A Survey》
No 7. 《Fair k-Means Clustering》
No 8. 《Discovering Symbolic Models from Deep Learning with Inductive Biases》
No 9. 《Knowledge-Aware Language Model Pretraining》
No 10. 《Differentiable Top-k Operator with Optimal Transport》
No 11. 《HRank: Filter Pruning using High-Rank Feature Map》
No 12. 《GhostNet: More Features from Cheap Operations》
No 13. 《SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness》
No 14. 《Statistical Mechanics of Generalization in Kernel Regression》
No 15. 《An EM Approach to Non-autoregressive Conditional Sequence Generation》
No 16. 《One Thousand and One Hours: Self-driving Motion Prediction Dataset》
No 17. 《Time-varying Graph Representation Learning via Higher-Order Skip-Gram with Negative Sampling》
No 18. 《Graph Optimal Transport for Cross-Domain Alignment》
No 19. 《Machine learning-based clinical prediction modeling -- A practical guide for clinicians》
No 20. 《Matern Gaussian processes on Riemannian manifolds》
No 21. 《Topological Insights in Sparse Neural Networks》
No 22. 《Stochastic Differential Equations with Variational Wishart Diffusions》
No 23. 《Pre-training via Paraphrasing》
No 24. 《MUMBO: MUlti-task Max-value Bayesian Optimization》
No 25. 《Fair Hierarchical Clustering》
No 26. 《Swapping Autoencoder for Deep Image Manipulation》
No 27. 《Making DensePose fast and light》
No 28. 《Subgraph Neural Networks》
No 29. 《I know why you like this movie: Interpretable Efficient Multimodal Recommender》
No 30. 《Sparse GPU Kernels for Deep Learning》

No 1. 《Debiased Contrastive Learning》
No 2. 《The Eyes Have It: An Integrated Eye and Face Model for Photorealistic Facial Animation》
No 3. 《Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary》
No 4.
《The Art of Natural Language Processing: Classical, Modern and Contemporary Approaches to Text Document Classification :: SSRN》
No 5. 《NVAE: A Deep Hierarchical Variational Autoencoder》
No 6. 《A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization》
No 7. 《ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network》
No 8. 《Knowledge Distillation Beyond Model Compression》
No 9. 《LSTM and GPT-2 Synthetic Speech Transfer Learning for Speaker Recognition to Overcome Data Scarcity》
No 10. 《Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search》
No 11. 《Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention》
No 12. 具有周期激活函数的隐式神经网络表示
No 13. 《3D Topology Transformation with Generative Adversarial Networks》
No 14. 《Big Self-Supervised Models are Strong Semi-Supervised Learners》
No 15. 《Early-Learning Regularization Prevents Memorization of Noisy Labels》
No 16. 《How benign is benign overfitting?》
No 17. 《The Global Landscape of Neural Networks: An Overview》
No 18. 《Language-agnostic BERT Sentence Embedding》
No 19.
《SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows》
No 20. 《The Measure of Intelligence》
No 21. 《Validation and generalization of pixel-wise relevance in convolutional neural networks trained for face classification》
No 22. 《The Go Transformer: Natural Language Modeling for Game Play》
No 23. 《Graph Neural Network Based Coarse-Grained Mapping Prediction》
No 24. 《Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval》
No 25. 《Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks》
No 26. 《DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference》
No 27. 《Collaborative Learning for Faster StyleGAN Embedding》
No 28.
《In Search of Lost Domain Generalization》
No 29. 《DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference》
No 30. 《Federated Learning with Compression: Unified Analysis and Sharp Guarantees》

No 1. 《Closed-Form Factorization of Latent Semantics in GANs》
No 2. 《Graph Structure of Neural Networks》
No 3. 《Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations》
No 4. 效果不错的像素图矢量化
No 5. 《Xiaomingbot: A Multilingual Robot News Reporter》
No 6. 《Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration》
No 7. 《Visualizing Transfer Learning》
No 8. 对比代码表示学习(ContraCode)
No 9. 《SegFix: Model-Agnostic Boundary Refinement for Segmentation》
No 10. 《Explainable Deep One-Class Classification》
No 11. 《Sudo rm -rf: Efficient Networks for Universal Audio Source Separation》
No 12. 《Contrastive Training for Improved Out-of-Distribution Detection》
No 13. 《Graph Neural Network Based Coarse-Grained Mapping Prediction》
No 14. 《The Computational Limits of Deep Learning》
No 15. 《A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection》
No 16. 《Video Object Segmentation with Episodic Graph Memory Networks》
No 17. 《Deep Reinforcement Learning and its Neuroscientific Implications》
No 18. 《Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations》
No 19.
《Meta-Learning Requires Meta-Augmentation》
No 20. 《Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP》
No 21. 《Deep Placental Vessel Segmentation for Fetoscopic Mosaicking》
No 22. 《Causal Inference using Gaussian Processes with Structured Latent Confounders》
No 23. 《A Survey of Privacy Attacks in Machine Learning》
No 24. 《D2D: Learning to find good correspondences for image matching and manipulation》
No 25. 《Uncertainty-Aware Lookahead Factor Models for Quantitative Investing》
No 26. 《Transfer Learning for Brain-Computer Interfaces: A Complete Pipeline》
No 27. 《RetrieveGAN: Image Synthesis via Differentiable Patch Retrieval》
No 28. 《ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation》
No 29. 《All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference》
No 30. 《Attack of the Tails: Yes, You Really Can Backdoor Federated Learning》

No 1. 《The Computational Limits of Deep Learning》
No 2. 《Learning from Noisy Labels with Deep Neural Networks: A Survey》
No 3. 《Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop》
No 4. 《Monte-Carlo Tree Search as Regularized Policy Optimization》
No 5. 《Towards Deeper Graph Neural Networks》
No 6. 《Xiaomingbot: A Multilingual Robot News Reporter》
No 7.
《Unsupervised Shape and Pose Disentanglement for 3D Meshes》
No 8. 《CheXphoto: 10,000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness》
No 9. 《Active Learning under Label Shift》
No 10. 《Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild》
No 11. 《Generating Person Images with Appearance-aware Pose Stylizer》
No 12.
《Deep Learning in Protein Structural Modeling and Design》
No 13. 《Visualizing Deep Graph Generative Models for Drug Discovery》
No 14. 《Whole-Body Human Pose Estimation in the Wild》
No 15. 《Shape and Viewpoint without Keypoints》
No 16. 《ProteiNN: Intrinsic-Extrinsic Convolution and Pooling for Scalable Deep Protein Analysis》
No 17.
《Contact and Human Dynamics from Monocular Video》
No 18. 《Generative Hierarchical Features from Synthesizing Images》
No 19. 《Do Adversarially Robust ImageNet Models Transfer Better?》
No 20. 《Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop》
No 21. 《D2D: Learning to find good correspondences for image matching and manipulation》
No 22.
《CrossTransformers: spatially-aware few-shot transfer》
No 23. 《A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum》
No 24. 《TSIT: A Simple and Versatile Framework for Image-to-Image Translation》
No 25. 《RetrieveGAN: Image Synthesis via Differentiable Patch Retrieval》
No 26. 《SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design》
No 27. 《Points2Surf: Learning Implicit Surfaces from Point Cloud Patches》
No 28.
《Accelerating 3D Deep Learning with PyTorch3D》
No 29. 《Path Signatures on Lie Groups》
No 30. 《Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks Via Nonlinear Multigrid》