tangxianfeng / PA-GNN
Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
☆20Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for PA-GNN
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆42Updated 3 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆26Updated 2 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆58Updated last year
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆19Updated 3 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated 11 months ago
- Adversarial Attacks on Node Embeddings via Graph Poisoning☆59Updated 4 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆40Updated 3 years ago
- The code of paper "Adversarial Label-Flipping Attack and Defense for Graph Neural Networks" (ICDM 2020)☆17Updated 3 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆19Updated 4 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆28Updated last year
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆18Updated 3 years ago
- Code for the paper "Quantifying Privacy Leakage in Graph Embedding" published in MobiQuitous 2020☆15Updated 2 years ago
- A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning☆12Updated 4 years ago
- Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22☆17Updated 2 years ago
- Adversarial training for Graph Neural Networks☆59Updated 3 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆91Updated last year
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆28Updated last year
- ☆12Updated 3 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 2 years ago
- Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure☆22Updated 4 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆143Updated 2 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆25Updated 2 years ago
- This is a Pytorch implementation of our "Learning on Attribute-Missing Graphs".☆28Updated 2 years ago
- A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models☆36Updated 3 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆51Updated 4 years ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 3 years ago
- The implementation of paper "Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks"☆11Updated 3 years ago
- ☆19Updated 2 years ago
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆127Updated 2 years ago
- Implementation of CIKM2020 -- Graph Prototypical Networks for Few-shot Learning on Attributed Networks☆47Updated 3 years ago