Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
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Updated
Jan 7, 2023 - Python
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
A scikit-learn compatible library for graph kernels
Papers about explainability of GNNs
Distributed Graph Analytics with Apache Flink
Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".
Implementation of the paper "NetGAN: Generating Graphs via Random Walks".
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…
Python implementation of frequent subgraph mining algorithm gSpan. Directed graphs are supported.
Papers about graph transformers.
Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)
A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).
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…
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
Papers on Graph Analytics, Mining, and Learning
A curated list of awesome graph representation learning.
A collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.
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