277 citations · 564 across the 48 of their papers we have counts for
3 papers · 1 filter
Deep FPF: Gain function approximation in high-dimensional setting
S. Yagiz Olmez, Amirhossein Taghvaei, Prashant G. Mehta
In this paper, we present a novel approach to approximate the gain function of the feedback particle filter (FPF). The exact gain function is the solution of a Poisson equation inv…
Accelerated Flow for Probability Distributions
Amirhossein Taghvaei, Prashant G. Mehta
This paper presents a methodology and numerical algorithms for constructing accelerated gradient flows on the space of probability distributions. In particular, we extend the recen…
Approximate dynamic programming using fluid and diffusion approximations with applications to power management
Wei Chen, Dayu Huang, Ankur A. Kulkarni +5
Neuro-dynamic programming is a class of powerful techniques for approximating the solution to dynamic programming equations. In their most computationally attractive formulations,…