CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

A repository of pretty cool datasets that I collected for network science and machine learning research.

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"

A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).

Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)

Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)

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

Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]

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

A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).

Topological Graph Neural Networks (ICLR 2022)

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Source code for EvalNE, a Python library for evaluating Network Embedding methods.

Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056

GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification (ICLR'22)

The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"