Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

A pytorch adversarial library for attack and defense methods on images and graphs

Papers about graph transformers.

Papers about explainability of GNNs

A scikit-learn compatible library for graph kernels

Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contribut…

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

Distributed Temporal Graph Analytics with Apache Flink

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

Python implementation of frequent subgraph mining algorithm gSpan. Directed graphs are supported.

Implementation of the paper "NetGAN: Generating Graphs via Random Walks".

Papers about out-of-distribution generalization on graphs.

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".

Papers on Graph Analytics, Mining, and Learning

Python Implementation for Random Walk with Restart (RWR)

GraMi is a novel framework for frequent subgraph mining in a single large graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi supports finding frequent subgraphs as well as frequent patterns, Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nod…

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

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

A collection of open-source and free machine learning resources