深度学习经典、新论文逐段精读

A pytorch library for graph and hypergraph computation.

A Graph Structure Learning (GSL) Toolkit

A collection of classified and organized top conference paper list.

Recommender System Papers

A multi-backend graph learning library.

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

A collection of research papers related to graph structure learning(GSL).

Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022

Contrastive Graph Structure Learning via Information Bottleneck for Recommendation

Book_6_《数据有道》 | 鸢尾花书：从加减乘除到机器学习；欢迎大家批评指正！纠错多的同学会得到赠书感谢！

Book_4_《矩阵力量》 | 鸢尾花书：从加减乘除到机器学习；上架！

A pytorch implementation of He et al. "Neural Collaborative Filtering" at WWW'17

pytorch version of NCF

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

A Python Library for Graph Outlier Detection (Anomaly Detection)

Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.

A powerful and flexible machine learning platform for drug discovery

《统计学习方法》的代码实现

This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

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

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

My future research

The PyTorch implementation of LightGCN

An Efficient and Unified Benchmark for GNN-based Recommendation.