fair-machine-learning

Repository for the AugmentedPCA Python package.

https://parulgupta1004.github.io/fair-seldonian/

Code and data for our demo "Efficient Fair Graph Representation Learning Using a Multi-level Framework" in WWW ’23.

📝 Implementation of our approach for balancing the utility of the decision maker and the fairness towards the decision subjects for a prediction-based decision-making system

📝 Exploring the gradual (in)compatibility of the fairness metrics independence, separation and sufficiency.

ICLR 2026 Paper

Code associated to our manuscript titled `Fair automated assessment of noncompliance in cargo ship networks'

Code and results for parameterized exact fair decision tree learning

End-to-End Python implementation of Medina-Olivares et.al's (2026) "findr" framework: a semi-structured credit-risk logit decomposing log-odds into an interpretable linear term and a QR-orthogonalised neural residual, trained with an in-processing Wasserstein fairness penalty and benchmarked on a score-level accuracy-fairness frontier.