Stars
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Graph Neural Network Library for PyTorch
PyTorch implementations of Generative Adversarial Networks.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
YSDA course in Natural Language Processing
Code for the paper "Jukebox: A Generative Model for Music"
Implementation of Graph Convolutional Networks in TensorFlow
A flexible framework of neural networks for deep learning
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法…
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
Repository containing notebooks of my posts on Medium
Message Passing Neural Networks for Molecule Property Prediction
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
How Powerful are Graph Neural Networks?
Sample Code for Gated Graph Neural Networks
Training neural models with structured signals.
[IJCAI'18] Spatio-Temporal Graph Convolutional Networks
A list of recent papers, libraries and datasets about 3D shape/scene analysis (by topics, updating).
Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
TensorFlow implementations of Graph Neural Networks