Counterfactually Fair Regression via Optimal Transport

M. Generali Lince, S. Gaucher, J-J. Vie +1

We consider the problem of learning a counterfactually fair regressor. We adopt a causal uncertainty view in which counterfactual fairness is defined with resampled noise. We focus…