isail-laboratory / iDEA-iSAIL-Reading-Group
☆26Updated 3 weeks ago
Alternatives and similar repositories for iDEA-iSAIL-Reading-Group
Users that are interested in iDEA-iSAIL-Reading-Group are comparing it to the libraries listed below
Sorting:
- ☆2Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆26Updated 2 years ago
- Open-source datasets for paper "Fairness in Graph Mining: A Survey".☆18Updated 2 years ago
- ☆9Updated 2 years ago
- ☆18Updated 3 years ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆64Updated last year
- ☆17Updated last year
- Code for paper https://arxiv.org/abs/2102.13186☆44Updated 4 years ago
- A curated list of resources for OOD detection with graph data.☆19Updated last year
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆28Updated 11 months ago
- Paper List for Fair Graph Learning (FairGL).☆136Updated 7 months ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated 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
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆63Updated last year
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆19Updated 2 years ago
- Open-source code for ''Individual Fairness for Graph Neural Networks: A Ranking based Approach''.☆12Updated 2 years ago
- Code for ICLR'2021 paper: On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections☆12Updated 3 years ago
- This is the implementation of OODGAT from KDD'22: Learning on Graphs with Out-of-Distribution Nodes.☆23Updated 2 years ago
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated 2 years ago
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆21Updated 4 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆32Updated 2 years ago
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆11Updated 7 months ago
- The official pytorch implementation of Propagation_then_Training for graph (https://arxiv.org/abs/2010.12408)☆26Updated 3 years ago
- ☆26Updated 2 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- ☆54Updated 7 months ago
- ☆24Updated 2 years ago
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year