A comprehensive AI fairness exploration framework.
- 📈 Fairness reports and stamps
- 🎏 Multivalue multiattribute
- 🛠️ Measure building blocks
- ⚙️ ML integration (
numpy,torch,tensorflow,jax)
FairBench strives to be compatible with the latest Python release, but compatibility delays of third-party ML libraries usually means that only the language's previous release is tested and stable (currently 3.12).
@article{krasanakis2024standardizing,
title={Towards Standardizing AI Bias Exploration},
author={Emmanouil Krasanakis and Symeon Papadopoulos},
year={2024},
eprint={2405.19022},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
Maintainer: Emmanouil (Manios) Krasanakis ([email protected])
License: Apache 2.0
Contributors: Giannis Sarridis
This project includes modified code originally licensed under the MIT License:
- ReBias. (Copyright © 2020-present NAVER Corp)
Modifications © 2024 Emmanouil Krasanakis.
See fairbench/bench/vision/datasets/mnist/ for details.
