Categorical and geometric methods in statistical, manifold, and machine learning

Abstract

We present and discuss applications of the category of probabilistic morphisms, initially developed in \cite{Le2023}, as well as some geometric methods to several classes of problems in statistical, machine and manifold learning which shall be, along with many other topics, considered in depth in the forthcoming book \cite{LMPT2024}.

37 p., will appear as part of a special volume in the Springer Tohoku Series in Mathematics