yixinliu233 / G-OOD-D
[WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
☆39Updated 2 years ago
Alternatives and similar repositories for G-OOD-D:
Users that are interested in G-OOD-D are comparing it to the libraries listed below
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated last year
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆20Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 10 months ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆40Updated last year
- [ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改善类别不平衡节点分类☆24Updated 4 months ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆30Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆28Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆22Updated last year
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆23Updated last year
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆42Updated 3 months ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆34Updated 2 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆35Updated last year
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆34Updated 5 months ago
- Code for TNNLS paper "Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions"☆14Updated last year
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆36Updated last year
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆45Updated 2 years ago
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆24Updated 2 months ago