xingchenwan / grabnelLinks
[NeurIPS '21] Adversarial Attacks on Graph Classification via Bayesian Optimisation (GRABNEL)
☆14Updated 4 years ago
Alternatives and similar repositories for grabnel
Users that are interested in grabnel are comparing it to the libraries listed below
Sorting:
- Adversarial attacks and defenses on Graph Neural Networks.☆391Updated last year
- Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)☆28Updated 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
- Adversarial training for Graph Neural Networks☆61Updated 4 years ago
- ☆56Updated 3 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆21Updated 5 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆71Updated 2 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆43Updated 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
- A curated collection of adversarial attack and defense on graph data.☆576Updated 2 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆29Updated 4 years ago
- code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)☆22Updated 4 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆90Updated last year
- ☆14Updated 4 years ago
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆130Updated 3 years ago
- Paper List for Fair Graph Learning (FairGL).☆144Updated last year
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆31Updated 2 years ago
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆20Updated 2 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
- Code for ICLR'2021 paper: On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections☆12Updated 4 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Updated 2 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
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆28Updated 3 years ago
- My future research☆416Updated 2 years ago
- Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".☆221Updated 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
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 4 years ago
- Papers about out-of-distribution generalization on graphs.☆168Updated 2 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆154Updated 4 years ago
- walk2friends: Inferring Social Links from Mobility Profiles☆22Updated 7 years ago