Popular GitHub Repositories for Heterophily

This repository contains the resources on graph neural network (GNN) considering heterophily.

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

NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework

Dir-GNN is a machine learning model that enables learning on directed graphs.

Gradient gating (ICLR 2023)

ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

[WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

Code for GBK-GNN (paper accepted by WWW2022)

A curated list of Heterophilous Graph Self-Supervised Learning papers.

How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)