In the Gaussian case, invariant features predicting Y independent of confounders Z are given by the top d eigenvectors of a matrix derived from the optimal transport barycenter of Z given Y.
Gender imbalance in medical imaging datasets produces biased classi- fiers for computer-aided diagnosis.Proceedings of the National Academy of Sciences, 117(23):12592–12594
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Invariant Feature Extraction Through Conditional Independence and the Optimal Transport Barycenter Problem: the Gaussian case
In the Gaussian case, invariant features predicting Y independent of confounders Z are given by the top d eigenvectors of a matrix derived from the optimal transport barycenter of Z given Y.