  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.
