sigeisler / robustness_of_gnns_at_scaleLinks
This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).
☆30Updated 2 years ago
Alternatives and similar repositories for robustness_of_gnns_at_scale
Users that are interested in robustness_of_gnns_at_scale are comparing it to the libraries listed below
Sorting:
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 3 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Updated last year
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆97Updated 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
- [ICML 2021] "A Unified Lottery Tickets Hypothesis for Graph Neural Networks", Tianlong Chen*, Yongduo Sui*, Xuxi Chen, Aston Zhang, Zhang…☆67Updated 2 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆71Updated 2 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆29Updated 3 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆29Updated 3 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆89Updated last year
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆116Updated 4 years ago
- This repository contains the official implementation of the paper "Reliable Graph Neural Networks via Robust Aggregation" (NeurIPS, 2020)…☆18Updated 3 years ago
- Official implementation of our FLAG paper (CVPR2022)☆145Updated 3 years ago
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated last month
- Official implementation of GOAT model (ICML2023)☆38Updated 2 years ago
- How Powerful are Spectral Graph Neural Networks☆74Updated 2 years ago
- Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)☆28Updated 4 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆42Updated 4 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆94Updated 2 years ago
- ☆26Updated 3 years ago
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆20Updated 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
- Paper List for Fair Graph Learning (FairGL).☆142Updated last year
- DP-GNN design that ensures both model weights and inference procedure differentially private (NeurIPS 2023)☆11Updated 2 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 3 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 2 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆65Updated last year
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆69Updated 2 years ago
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆49Updated 2 years ago
- Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"☆13Updated 4 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year