A curated list of adversarial attacks and defenses papers on graph-structured data.
☆861Dec 15, 2023Updated 2 years ago
Alternatives and similar repositories for graph-adversarial-learning-literature
Users that are interested in graph-adversarial-learning-literature are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A curated collection of adversarial attack and defense on graph data.☆588Nov 7, 2023Updated 2 years ago
- Adversarial attacks and defenses on Graph Neural Networks.☆394Feb 22, 2024Updated 2 years ago
- A pytorch adversarial library for attack and defense methods on images and graphs☆1,085Jun 26, 2025Updated last year
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆157Dec 9, 2021Updated 4 years ago
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆129Jul 16, 2022Updated 3 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".☆227May 31, 2022Updated 4 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆30Jan 11, 2022Updated 4 years ago
- Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).☆1,728Feb 2, 2024Updated 2 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆100Nov 6, 2023Updated 2 years ago
- Adversarial Attacks on Node Embeddings via Graph Poisoning☆59Dec 23, 2019Updated 6 years ago
- Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"☆308May 12, 2023Updated 3 years ago
- Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track☆22Aug 19, 2024Updated last year
- Adversarial training for Graph Neural Networks☆62Feb 26, 2021Updated 5 years ago
- A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources☆1,861Jun 29, 2026Updated last week
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- links to conference publications in graph-based deep learning☆5,075Jun 7, 2026Updated 3 weeks ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆89Oct 15, 2024Updated last year
- A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models☆35May 26, 2021Updated 5 years ago
- ☆57Oct 5, 2022Updated 3 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Nov 27, 2023Updated 2 years ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Nov 17, 2022Updated 3 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆74Jul 6, 2023Updated 2 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆31Jul 25, 2023Updated 2 years ago
- ☆18Jan 12, 2022Updated 4 years ago
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)☆23Nov 5, 2021Updated 4 years ago
- Must-read papers on graph neural networks (GNN)☆16,809Dec 20, 2023Updated 2 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆43Dec 7, 2020Updated 5 years ago
- A Deep Graph-based Toolbox for Fraud Detection☆757Apr 20, 2022Updated 4 years ago
- A curated list of graph data augmentation papers.☆314Apr 17, 2024Updated 2 years ago
- Benchmark datasets, data loaders, and evaluators for graph machine learning☆2,090May 6, 2025Updated last year
- A list of backdoor learning resources☆1,177Jul 31, 2024Updated last year
- An official PyTorch implementation of "Unnoticeable Backdoor Attacks on Graph Neural Networks" (WWW 2023)☆62Dec 3, 2023Updated 2 years ago
- Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric☆925Dec 20, 2023Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆495Dec 5, 2018Updated 7 years ago
- Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020☆401Jun 17, 2024Updated 2 years ago
- Papers about explainability of GNNs☆811Jun 3, 2026Updated last month
- GraphGallery is a gallery for benchmarking Graph Neural Networks☆475Aug 14, 2023Updated 2 years ago
- Repository for benchmarking graph neural networks (JMLR 2023)☆2,663Jun 22, 2023Updated 3 years ago
- gnn explainer☆1,052Aug 30, 2024Updated last year
- Papers about out-of-distribution generalization on graphs.☆169Jun 5, 2023Updated 3 years ago