EnyanDai / SEGNN
A PyTorch implementation of "Towards Self-Explainable Graph Neural Network" (CIKM 2021).
☆11Updated 3 years ago
Alternatives and similar repositories for SEGNN:
Users that are interested in SEGNN are comparing it to the libraries listed below
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆47Updated 2 years ago
- Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)☆123Updated last year
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 3 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆65Updated 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
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆133Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆41Updated 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
- Contrastive Attributed Network Anomaly Detection with Data Augmentation (PAKDD'22)☆25Updated 2 years ago
- Imbalanced Network Embedding vi aGenerative Adversarial Graph Networks☆27Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year
- Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"☆54Updated 3 years ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 2 years ago
- This is a Pytorch implementation of our "Learning on Attribute-Missing Graphs".☆28Updated 2 years ago
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆35Updated last year
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆28Updated 3 years ago
- Code for paper "Mixup for Node and Graph Classification", WWW 2021☆46Updated 3 years ago
- Deeper insights into graph convolutional networks for semi-supervised learning☆19Updated 6 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆80Updated last year
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆62Updated 8 months ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆87Updated 3 years ago
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆60Updated 3 years ago
- dynamic graph/network embedding/representation methods☆16Updated 4 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆33Updated 2 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 2 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆88Updated 3 years ago
- ☆24Updated 2 years ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆23Updated last year
- Official code of "Towards Multi-Grained Explainability for Graph Neural Networks" (NeurIPS 2021) + Pytorch Implementation of recent attri…☆68Updated last year