Variational: Calculus (springer Monographs In Ma...

"Variational Calculus" by Florens, Mouchart, and Rolin (Springer Monographs in Mathematics) bridges classical functional analysis with modern Bayesian statistics, utilizing Hilbert spaces and variational operators for statistical modeling. It provides a foundational framework for variational inference in machine learning, exploring how to approximate complex probability distributions through functional derivatives. More information on this monograph can be found on the Springer website.