BUPT-GAMMA / LafAK
The code of paper "Adversarial Label-Flipping Attack and Defense for Graph Neural Networks" (ICDM 2020)
☆17Updated 4 years ago
Alternatives and similar repositories for LafAK:
Users that are interested in LafAK are comparing it to the libraries listed below
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆64Updated last year
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆28Updated 3 years ago
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated last year
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 4 years ago
- ☆22Updated 2 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
- 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
- Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"☆13Updated 3 years ago
- Code for the paper "Quantifying Privacy Leakage in Graph Embedding" published in MobiQuitous 2020☆15Updated 3 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆85Updated 5 months ago
- Imbalanced Network Embedding vi aGenerative Adversarial Graph Networks☆27Updated 3 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆30Updated last year
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆62Updated last year
- An official PyTorch implementation of "Unnoticeable Backdoor Attacks on Graph Neural Networks" (WWW 2023)☆57Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 2 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆37Updated 3 years ago
- Code for paper https://arxiv.org/abs/2102.13186☆44Updated 4 years ago
- Official implementation of "Graph Unlearning" (ACM CCS 2022)☆45Updated 2 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆26Updated 2 years ago
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆47Updated last year
- 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
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆92Updated last year
- Code for Neurips2021 Paper "Topology-Imbalance Learning for Semi-Supervised Node Classification".☆55Updated 3 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆32Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆18Updated 3 years ago
- Official Code Repository for the paper - Personalized Subgraph Federated Learning (ICML 2023)☆47Updated last year