THUDM / tdgiaLinks
code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)
☆21Updated 3 years ago
Alternatives and similar repositories for tdgia
Users that are interested in tdgia are comparing it to the libraries listed below
Sorting:
- Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track☆22Updated last year
- ☆21Updated 3 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆96Updated last year
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆29Updated 3 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆71Updated 2 years ago
- The relevant codes for "GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections".☆14Updated last year
- Paper List for Fair Graph Learning (FairGL).☆141Updated last year
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- ☆26Updated last year
- Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22☆17Updated 3 years ago
- Codes and data for KDD 2022 Research Track paper "CLARE: A Semi-supervised Community Detection Algorithm"☆36Updated 2 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆40Updated 4 years ago
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆28Updated last year
- The source code of SpCo☆35Updated 2 years ago
- Adversarial training for Graph Neural Networks☆61Updated 4 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆33Updated 3 years ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆67Updated 2 years ago
- Codebase used to generate the results for NeurIPS23 "Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directi…☆11Updated last year
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆20Updated 2 years ago
- A PyTorch implementation of "Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?" (KDD 2025)☆25Updated 3 months ago
- Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)☆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
- Code listing for the paper 'Heterogeneity-aware Twitter Bot Detection with Relational Graph Transformers'. AAAI 2022.☆37Updated 3 years ago
- Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)☆130Updated 3 years ago
- ☆26Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆27Updated 3 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆87Updated 11 months ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆81Updated 4 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆89Updated 3 years ago
- Adversarial attacks and defenses on Graph Neural Networks.☆385Updated last year