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fairness-awareness-model
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A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰
Official implementation of our work "Collaborative Fairness in Federated Learning."
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
Paper lists about 'Constitutional AI System' or 'AI under Ethical Guidelines'
Official implementation of "FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Records" (MLHC 2024)
Fairness accountable regression in Matlab
implementation of fair dummies
Tensorflow constrained optimization with different Deep Learning Models
Package implementing methods developed in "Preventing Fairness Gerrymandering" [ICML '18], "Rich Subgroup Fairness for Machine Learning" [ FAT* '19]. active development fork @algowatchupenn
Mitigate machine learning bias to ensure data ethics in U.S. national home mortgage dataset.
Analyze borrower data and enhance decision-making for financial institutions, focusing on mitigating risks, ensuring fairness, and maintaining transparency and regulatory compliance.
Official code for "FairFedOph: Group Fairness-aware Federated Learning Benchmark for Ophthalmic Imaging"