PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, wav2lip, picture repair, image editing, photo2cartoon, image style transfer, and so on.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Geometric Deep Learning Extension Library for PyTorch

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)

A collection of important graph embedding, classification and representation learning papers with implementations.

This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

Deep Learning Visualization Toolkit（『飞桨』深度学习可视化工具 ）

Github page for the paper "Variational Recurrent Neural Networks for Graph Classification" presented at the RLGM workshop of ICLR 2019

Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks

The PyTorch implementation of LightGCN

中文医疗NLP领域 数据集，论文 ，知识图谱，语料，工具包

A Large-scale Chinese Short-Text Conversation Dataset and Chinese pre-training dialog models

图神经网络相关算法详述及实现

How Powerful are Graph Neural Networks?

Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x

项亮的《推荐系统实践》的代码实现

《深入浅出图神经网络：GNN原理解析》配套代码

Must-read papers on graph neural networks (GNN)

Repository for benchmarking graph neural networks

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…

Representation learning on large graphs using stochastic graph convolutions.

Papers on Graph neural network(GNN)

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