ChandlerBang / pytorch-gnn-meta-attack
Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.
☆21Updated 3 years ago
Alternatives and similar repositories for pytorch-gnn-meta-attack:
Users that are interested in pytorch-gnn-meta-attack are comparing it to the libraries listed below
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆27Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆26Updated 2 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆60Updated last year
- Code for paper https://arxiv.org/abs/2102.13186☆43Updated 3 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 2 years ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆60Updated last year
- 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
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆37Updated 4 years ago
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆20Updated last year
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆28Updated last year
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆18Updated 3 years ago
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆27Updated 7 months ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated last year
- Code for paper "Mixup for Node and Graph Classification", WWW 2021☆45Updated 3 years ago
- ☆22Updated 2 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆32Updated 2 years ago
- How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)☆12Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆41Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆42Updated 2 years ago
- Imbalanced Network Embedding vi aGenerative Adversarial Graph Networks☆26Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 3 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆62Updated 8 months ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆84Updated 2 years ago
- ☆28Updated 3 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆33Updated 2 years ago
- ☆25Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year