KaidiXu / GCN_ADV_Train
Adversarial training for Graph Neural Networks
☆59Updated 3 years ago
Alternatives and similar repositories for GCN_ADV_Train:
Users that are interested in GCN_ADV_Train are comparing it to the libraries listed below
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆127Updated 2 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆146Updated 3 years ago
- Adversarial Attacks on Node Embeddings via Graph Poisoning☆59Updated 5 years ago
- Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".☆220Updated 2 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆28Updated 3 years ago
- A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models☆36Updated 3 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆42Updated 4 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆60Updated last year
- code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)☆19Updated 3 years ago
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 3 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆92Updated last year
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆36Updated 3 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated last year
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆29Updated last year
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆85Updated 4 months ago
- ☆18Updated 3 years ago
- Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".☆20Updated 4 years ago
- Official implementation of our FLAG paper (CVPR2022)☆142Updated 2 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…☆24Updated 2 years ago
- Adversarial attacks and defenses on Graph Neural Networks.☆376Updated last year
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆37Updated 4 years ago
- The source code for NeurIPS 2020 paper "Graph Policy Network for Transferable Active Learning on Graphs"☆45Updated 4 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆19Updated 4 years ago
- Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22☆17Updated 2 years ago
- ☆53Updated 2 years ago
- This is a sample implementation of "Robust Graph Convolutional Networks Against Adversarial Attacks", KDD 2019.☆11Updated 4 years ago
- Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track☆21Updated 6 months ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆60Updated last year
- Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)☆26Updated 3 years ago