ZhixunLEE / FairGB
[SIGKDD 2024] Rethinking Fair Graph Neural Networks from Re-balancing
☆10Updated 9 months ago
Alternatives and similar repositories for FairGB
Users that are interested in FairGB are comparing it to the libraries listed below
Sorting:
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆22Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- A curated list of papers on graph transfer learning (GTL).☆17Updated last year
- Open Source Code for GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models (KDD'24)☆25Updated 10 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆30Updated last year
- The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs☆28Updated 9 months ago
- Code for ICLR'24 Paper "Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks"☆10Updated last year
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆43Updated 4 months ago
- Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"☆30Updated this week
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆37Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆30Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 11 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- Official implementation of MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning☆17Updated last year
- ☆26Updated 8 months 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
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- ☆18Updated 3 months ago
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆35Updated 6 months ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆51Updated 2 years ago
- ☆22Updated 7 months ago
- The source code of SpCo☆35Updated last year
- ☆15Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- Code for SGDD☆25Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆39Updated 2 years ago
- [NeurIPS'24] ARC: A Generalist Graph Anomaly Detector with In-Context Learning☆21Updated 6 months ago
- Official implementation of paper "Efficient Tuning and Inference for Large Language Models on Textual Graphs"☆32Updated 10 months ago
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆32Updated 6 months ago