Continuous transformations of probability measures and their transport representations

Abstract

Given a function $F$ transforming a probability measure $\mu$ into another one $F(\mu)$, we study the existence and regularity of a transport representation of it. That is, we ask whether we can represent the image $F(\mu)$ of the input probability measure $\mu$ as the push-forward of $\mu$ by a map $f(\cdot,\mu)$ which may depend on $\mu$; and furthermore, how regular $f$ can be chosen depending on $F$. Even if $F$ is continuous and a transport representative exists, it cannot necessarily be chosen in a continuous way; however, if $F$ is Lipschitz continuous with respect to the Wasserstein distance, then $f$ can be chosen continuous. We provide several examples to illustrate the sharpness of our assumptions. This question is motivated by approximation results for transformations of probability distributions with transformers.