yushundong / Fairness-must-read-listLinks
Papers on fairness
☆12Updated 4 years ago
Alternatives and similar repositories for Fairness-must-read-list
Users that are interested in Fairness-must-read-list are comparing it to the libraries listed below
Sorting:
- Official implementation for KDD'22 paper "Learning Fair Representation via Distributional Contrastive Disentanglement"☆23Updated 3 years ago
- Open-source datasets for paper "Fairness in Graph Mining: A Survey".☆18Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- Code and data for the KDD 2023 paper "Predicting Information Pathways Across Online Communities."☆23Updated 8 months ago
- Facilitating learning, using, and designing graph processing pipelines/models systematically.☆27Updated 3 years ago
- UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs (KDD'25)☆18Updated 3 months ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆27Updated 3 years ago
- ☆14Updated 2 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago
- An Open and Unified Benchmark for Graph Condensation (submitted to NeurIPS 2024 Datasets and Benchmarks Track)☆19Updated last year
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆61Updated 2 years ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆67Updated 2 years ago
- Open-source code for ''Individual Fairness for Graph Neural Networks: A Ranking based Approach''.☆12Updated 3 years ago
- Official repository for NeurIPS'23 paper: GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation☆17Updated last year
- ☆29Updated last week
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago
- WWW 2024: New Frontiers of Knowledge Graph Reasoning: Recent Advances and Future Trends☆18Updated last year
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆70Updated 3 years ago
- ☆26Updated 2 years ago
- ☆35Updated 2 years ago
- ☆18Updated 3 years ago
- Code for ICLR'2021 paper: On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections☆12Updated 4 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆63Updated last year
- Paper List for Fair Graph Learning (FairGL).☆141Updated last year
- List of Publications in Graph Contrastive Learning☆34Updated 3 years ago
- Contrastive Graph Structure Learning via Information Bottleneck for Recommendation☆30Updated 2 years ago
- Code for ICML 2022 paper: Achieving Fairness at No Utility Cost via Data Reweighing with Influence☆12Updated 3 years ago
- ☆11Updated 4 years ago
- ☆20Updated 3 years ago
- ☆35Updated 2 years ago