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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
PyTorch Tutorial for Deep Learning Researchers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Graph Neural Network Library for PyTorch
Implementation of Graph Convolutional Networks in TensorFlow
A Library for Advanced Deep Time Series Models.
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
A collection of important graph embedding, classification and representation learning papers with implementations.
An implementation of a deep learning recommendation model (DLRM)
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
A PyTorch Library for Meta-learning Research
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
This package contains deep learning models and related scripts for RoseTTAFold
Actively maintained, pure Python wrapper for the Twitter API. Supports both normal and streaming Twitter APIs.
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
A command line tool (and Python library) for archiving Twitter JSON
Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).
PyGCL: A PyTorch Library for Graph Contrastive Learning
official implementation for the paper "Simplifying Graph Convolutional Networks"
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models