KTTRCDL / graph-feature-selectionLinks
[ICLR 2025] Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting
☆11Updated 2 months ago
Alternatives and similar repositories for graph-feature-selection
Users that are interested in graph-feature-selection are comparing it to the libraries listed below
Sorting:
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆60Updated 2 years ago
- The implementation for DropMessage.☆37Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated last year
- KDD23 - Classification of Edge-Dependent Labels of Nodes in Hypergraphs☆18Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆27Updated 10 months ago
- A Comprehensive Benchmark of Imbalanced Graph Learning (Accepted by ICLR 2025 Spotlight)☆10Updated 4 months ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- A curated list of awesome graph structure learning approaches☆39Updated 9 months ago
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆119Updated last year
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆89Updated 10 months ago
- I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs (AAAI'23)☆37Updated last year
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago
- the code of MoG☆19Updated last year
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆93Updated last year
- Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning☆19Updated last year
- [CIKM'24] Self-Supervision Improves Diffusion Models for Tabular Data Imputation☆14Updated 11 months ago
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆102Updated last year
- A curated list of papers on graph structure learning (GSL).☆49Updated 8 months ago
- [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☆25Updated 9 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆34Updated 2 years ago
- [CIKM 2023] Code for the paper "LTE4G: Long-Tail Experts for Graph Neural Networks"☆40Updated 3 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆43Updated 2 years ago
- A curated list of papers on graph transfer learning (GTL).☆17Updated last year