tangxianfeng / PA-GNN
Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
☆20Updated 5 years ago
Alternatives and similar repositories for PA-GNN:
Users that are interested in PA-GNN are comparing it to the libraries listed below
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆43Updated 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
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆63Updated last year
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆28Updated 3 years ago
- A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning☆12Updated 5 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated last year
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆19Updated 4 years ago
- Adversarial Attacks on Node Embeddings via Graph Poisoning☆60Updated 5 years ago
- Adversarial training for Graph Neural Networks☆60Updated 4 years ago
- Code for the paper "Quantifying Privacy Leakage in Graph Embedding" published in MobiQuitous 2020☆15Updated 3 years ago
- Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22☆17Updated 2 years ago
- A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models☆36Updated 3 years ago
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆18Updated 3 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆30Updated last year
- The code of paper "Adversarial Label-Flipping Attack and Defense for Graph Neural Networks" (ICDM 2020)☆17Updated 4 years ago
- Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure☆22Updated 5 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆146Updated 3 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆92Updated last year
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆51Updated 4 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆41Updated 3 years ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆128Updated 2 years ago
- ☆18Updated 3 years ago
- ☆12Updated 4 years ago
- First and Complementary Neighborhood Combination of Adjacency Matrix for Graph Learning☆20Updated last year
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- [ICML 2021] Information Obfuscation of Graph Neural Networks☆36Updated 3 years ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 3 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago
- Official implementation of our FLAG paper (CVPR2022)☆143Updated 2 years ago