Title: On Some Extensions of the Boué-Dupuis Variational Formula

Abstract: The Bou\'e-Dupuis variational formula gives a representation for log Laplace transforms of bounded measurable functions of a finite dimensional Brownian motion on a compact time interval as an infimum of a suitable cost over a collection of non-anticipative control processes. This variational formula has proved to be very useful in studying a variety of large deviation problems. In this article we collect some extensions of this basic result that have appeared in disparate venues in studying a broad range of large deviation questions. Some of these results can be found in a unified way in the recent book (Budhiraja and Dupuis(2019)), while others, to date, have been scattered at various places in the literature. The latter category includes, in particular, variational representations, when the stochastic dynamical system of interest has in addition to a driving L\'evy noise, another source of randomness, e.g. due to a random initial condition; when the functionals of interest depends on infinite-length paths of a L\'evy process; when the noise process is a Gaussian process with long-range dependence, e.g. a fractional Brownian motion, etc. The goal of this survey article is to present these diverse variational formulas in a systematic manner.