FairDrop
December 13, 2021 ยท View on GitHub
This is the companion code for the paper:
Spinelli I, Scardapane S, Hussain A, Uncini A, FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning, IEEE Transactions on Artificial Intelligence 2021.
Fair edge dropout
We introduce a flexible biased edge dropout algorithm for enhancing fairness in graph representation learning. FairDrop targets the negative effect of the network's homophily w.r.t the sensitive attribute.

Acknowledgments
Many thanks to the authors of [1] for making their code public and to the maintainers [3] for such an awesome open-source library.
Cite
Please cite our paper if you use this code in your own work:
@ARTICLE{spinelli2021fairdrop,
author={Spinelli, Indro and Scardapane, Simone and Hussain, Amir and Uncini, Aurelio},
journal={IEEE Transactions on Artificial Intelligence},
title={FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning},
year={2021},
volume={},
number={},
pages={1-1},
doi={10.1109/TAI.2021.3133818}}