BUPT-GAMMA / LafAKLinks
The code of paper "Adversarial Label-Flipping Attack and Defense for Graph Neural Networks" (ICDM 2020)
☆18Updated 4 years ago
Alternatives and similar repositories for LafAK
Users that are interested in LafAK are comparing it to the libraries listed below
Sorting:
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆29Updated 4 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆71Updated 2 years ago
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆49Updated 2 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆90Updated last year
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Updated 2 years ago
- Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"☆13Updated 4 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆31Updated 2 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆43Updated 4 years ago
- 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 is the implementation of Federated Graph Classification over Non-IID Graphs.☆45Updated 2 years ago
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 5 years ago
- Code for the paper "Quantifying Privacy Leakage in Graph Embedding" published in MobiQuitous 2020☆17Updated 4 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆28Updated 3 years ago
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 4 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆98Updated 2 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆21Updated 5 years ago
- 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
- ☆25Updated 3 years ago
- FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR…☆183Updated 2 years ago
- The implementation of paper "Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks"☆13Updated 4 years ago
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆20Updated 4 years ago
- This repository aims to provide links to works about privacy attacks and privacy preservation on graph data with Graph Neural Networks (G…☆23Updated 2 years ago
- ☆27Updated 3 years ago
- Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)☆28Updated 4 years ago
- ☆14Updated 4 years ago
- Official Code Repository for the paper - Personalized Subgraph Federated Learning (ICML 2023)☆52Updated 2 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆43Updated 5 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 3 years ago
- ☆97Updated last year