Zheda (Marco) Mai's repositories
CompBench
CompBench evaluates the comparative reasoning of multimodal large language models (MLLMs) with 40K image pairs and questions across 8 dimensions of relative comparison: visual attribute, existence, state, emotion, temporality, spatiality, quantity, and quality. CompBench covers diverse visual domains, including animals, fashion, sports, and scenes.
starting-kit
Starting kit for the NeurIPS 2023 unlearning challenge
online-continual-learning
A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and an online continual learning survey (Neurocomputing).
Hindsight
Code release for "Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception" [ICLR 2022]
bevfusion
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
TransFusion
[PyTorch] Official implementation of CVPR2022 paper "TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers". https://arxiv.org/abs/2203.11496
Awesome-Incremental-Learning
Awesome Incremental Learning
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
continual_learning_papers
Relevant papers in Continual Learning
mammoth
An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
CVPR20_CLVision_challenge
1'st Place approach for CVPR 2020 Continual Learning Challenge
Maximally_Interfered_Retrieval
Codebase for "Online Continual Learning with Maximally Interfered Retrieval"
fucking-algorithm
手把手撕LeetCode题目，扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.
data-science-interview-questions-and-answers
Data science interview questions with answers. Not ideally (yet)
Deep-AutoEncoder-Recommendation
Keras implementation of AutoRec and DeepRecommender from Nvidia.
120-Data-Science-Interview-Questions
Answers to 120 commonly asked data science interview questions.
practicalAI
📚 A practical approach to machine learning.
Keras-GAN
Keras implementations of Generative Adversarial Networks.
zhusuan
A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow