Mark12Ding / GNN-Practical-AttackLinks
Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)
☆28Updated 4 years ago
Alternatives and similar repositories for GNN-Practical-Attack
Users that are interested in GNN-Practical-Attack are comparing it to the libraries listed below
Sorting:
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 3 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆31Updated 2 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆98Updated 2 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆71Updated 2 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Updated 2 years ago
- Adversarial training for Graph Neural Networks☆61Updated 4 years ago
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 4 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆29Updated 4 years ago
- code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)☆22Updated 4 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆43Updated 4 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆90Updated last year
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆69Updated 2 years ago
- Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22☆17Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆28Updated 3 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆154Updated 4 years ago
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆20Updated 4 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Updated 3 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆138Updated 3 years ago
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆130Updated 3 years ago
- Codebase used to generate the results for NeurIPS23 "Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directi…☆11Updated 2 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆21Updated 5 years ago
- Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track☆22Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [NeurIPS '21] Adversarial Attacks on Graph Classification via Bayesian Optimisation (GRABNEL)☆14Updated 4 years ago
- Official repository for AAAI'23 paper: Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinf…☆29Updated 3 years ago
- Paper List for Fair Graph Learning (FairGL).☆144Updated last year
- This repository contains the official implementation of the paper "Reliable Graph Neural Networks via Robust Aggregation" (NeurIPS, 2020)…☆18Updated 3 years ago
- ☆27Updated 3 years ago
- ☆56Updated 3 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 3 years ago