Sishuo Chen's repositories
arxiv-helper
基于arxiv的论文检索和阅读工具
LogLinearTextClassification
Log Linear Model in Pure Python For Text Classification (EMNLP course project,PKU,spring 2020)
Meta-Learning-ABC
Introduction Materials about Meta Learning
SemanticParsingProject
Graph-based semantic dependence parsing project in pure Python (SemEval-2014 Task 8)
ALiPy
ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.
auto-sklearn
Automated Machine Learning with scikit-learn
Awesome-Meta-Learning
A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.
awesome-video-text-retrieval
A curated list of deep learning resources for video-text retrieval.
BLIP
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
chinese-poetry
The most comprehensive database of Chinese poetry 🧶最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人，21050首词。
FedMNMT
[Findings of ACL 2023] Communication Efficient Federated Learning for Multilingual Machine Translation with Adapter
FSSD_OoD_Detection
Feature Space Singularity for Out-of-Distribution Detection.
gitignore
A collection of useful .gitignore templates
PKUCSS.github.io
Personal site of Sishuo Chen
PKUCSS.github.io-backup
Personal Blog Of Sishuo Chen
pkuthss
LaTeX template for dissertations in Peking University
pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
PyMuPDF
Python bindings for MuPDF's rendering library.
pytorch-adversarial-training
PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.
pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
SeaNet-PyTorch
This repository is a PyTorch version of "Soft-edge Assisted Network for Single Image Super-Resolution". (IEEE TIP 2020)
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
TTSR
[CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution
visdcc
Dash Core Components for Visualization.