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Backward Nonlinear Smoothing Diffusions

Authors
  • Anderson, Brian D. O.
  • Bishop, Adrian N.
  • Del Moral, Pierre
  • Palmier, Camille
Type
Published Article
Publication Date
Oct 31, 2019
Submission Date
Oct 31, 2019
Identifiers
DOI: 10.1137/S0040585X97T99037X
Source
arXiv
License
Yellow
External links

Abstract

We present a backward diffusion flow (i.e. a backward-in-time stochastic differential equation) whose marginal distribution at any (earlier) time is equal to the smoothing distribution when the terminal state (at a latter time) is distributed according to the filtering distribution. This is a novel interpretation of the smoothing solution in terms of a nonlinear diffusion (stochastic) flow. This solution contrasts with, and complements, the (backward) deterministic flow of probability distributions (viz. a type of Kushner smoothing equation) studied in a number of prior works. A number of corollaries of our main result are given including a derivation of the time-reversal of a stochastic differential equation, and an immediate derivation of the classical Rauch-Tung-Striebel smoothing equations in the linear setting.

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