Applying the informative/non-informative decomposition to separated airfoil flows yields time-varying structures tied to future lift, but the bijective network makes maximal informativeness a built-in property, so the causality claim is structural rather than discovered.
J.,Principles of helicopter aerodynamics, Cambridge university press, 2006
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Information-theoretic machine learning for time-varying mode decomposition of separated aerodynamic flows
Applying the informative/non-informative decomposition to separated airfoil flows yields time-varying structures tied to future lift, but the bijective network makes maximal informativeness a built-in property, so the causality claim is structural rather than discovered.