HeavyMakeup/Bias-conflicting
2 papers with code • 1 benchmarks • 1 datasets
CelebA
Most implemented papers
EnD: Entangling and Disentangling deep representations for bias correction
EIDOSlab/entangling-disentangling-bias
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CVPR 2021
Artificial neural networks perform state-of-the-art in an ever-growing number of tasks, and nowadays they are used to solve an incredibly large variety of tasks.
FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations
gsarridis/flac
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To overcome these limitations, this work introduces FLAC, a methodology that minimizes mutual information between the features extracted by the model and a protected attribute, without the use of attribute labels.
