Variational representations for continuous time processes

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Large and Moderate Deviation Principles for McKean-Vlasov SDEs with Jumps (2020, methodology): “et O⊆ S. We endow MFC(S) with the weakest topology such that for each f∈ Cc(S) the mapping µ∈ MFC(S) → R S f(s)µ(ds) is continuous. This topology is metrizable such that MFC(S) is a Polish space, see [6] for more details. We ﬁx T >0 throughout this paper. Let Kbe a separable Hilbert space with in”
A Moderate Deviation Principle for 2-D Stochastic Navier-Stokes Equations Driven by Multiplicative L\'evy Noises (2015, unknown): “[4]).”
Large deviations for neutral functional SDEs with jumps (2015, methodology): “[7] some additional notation and notions.”
Moderate Deviation Principles for Stochastic Differential Equations with Jumps (2014, background): “As in [8], the starting point is the variational representation for expectations of positive functionals of a PRM from [11].”
Large deviation properties of weakly interacting processes via weak convergence methods (2010, background): “A key step to make the approach work is a variational representation of Poisson functionals, which has recently been established in [8].”
Large Deviations for Stochastic Partial Differential Equations Driven by a Poisson Random Measure (2012, methodology): “The variational representation from [9] is recalled and also a general large deviation result established in that paper is presented.”