18 citations · 32 across the 10 of their papers we have counts for
Showing math.OCShow all
3 papers · 1 filter
math.OC2024
Revisiting Stochastic Realization Theory using Functional Itô Calculus
Tanya Veeravalli, Maxim Raginsky
This paper considers the problem of constructing finite-dimensional state space realizations for stochastic processes that can be represented as the outputs of a certain type of a…
math.OC2023
A Constructive Approach to Function Realization by Neural Stochastic Differential Equations
Tanya Veeravalli, Maxim Raginsky
The problem of function approximation by neural dynamical systems has typically been approached in a top-down manner: Any continuous function can be approximated to an arbitrary ac…
math.OC2022
Nonlinear controllability and function representation by neural stochastic differential equations
Tanya Veeravalli, Maxim Raginsky
There has been a great deal of recent interest in learning and approximation of functions that can be expressed as expectations of a given nonlinearity with respect to its random i…