How does whitening transform affect downstream machine learning models?

Whitening removes correlations and equalizes variance across features.

Whitening transforms data so that features are uncorrelated and have unit variance. This can improve convergence in gradient-based models by making optimization landscapes more isotropic, but it may reduce interpretability and sometimes remove useful structure.