LirongWu / Homophily-Enhanced-Self-supervisionLinks
Code for TNNLS paper "Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions"
☆15Updated last year
Alternatives and similar repositories for Homophily-Enhanced-Self-supervision
Users that are interested in Homophily-Enhanced-Self-supervision are comparing it to the libraries listed below
Sorting:
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- [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 2 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆43Updated 2 years ago
- PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"☆15Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆42Updated 2 years ago
- The code of "Attribute and Structure preserving Graph Contrastive Learning" (AAAI 2023 oral)☆20Updated 4 months ago
- ☆28Updated 4 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆25Updated 5 months ago
- [TNNLS 2023] An official source code for paper "Simple Contrastive Graph Clustering".☆37Updated 5 months ago
- [KDD 2024] Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective☆16Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆84Updated 8 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- [WSDM 2022] Efficient Graph Convolution for Joint Node Representation Learning and Clustering☆19Updated last year
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆87Updated 9 months ago
- Code for GBK-GNN (paper accepted by WWW2022)☆16Updated 3 years ago
- A collection of papers on Graph Structural Learning (GSL)☆55Updated last year
- Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"☆35Updated 3 months ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆24Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆33Updated last year
- ☆11Updated 2 years ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆142Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- Pytorch implementation of "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes"☆18Updated 3 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated last year
- Neighbor Contrastive Learning on Learnable Graph Augmentation☆37Updated last year
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆65Updated last year