Parameter estimation in stochastic differential equations via Wiener chaos expansion and stochastic gradient descent

Francisco Delgado-Vences

doi:10.1016/j.apm.2026.117236

Parameter estimation in stochastic differential equations via Wiener chaos expansion and stochastic gradient descent

2026-07-31

0

OA

AI

F

Francisco Delgado-Vences *

J

Jose Julian Pavon-Español

A

Arelly Ornelas

DOI：10.1016/j.apm.2026.117236

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Abstract

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• Parameter estimation in SDEs via Wiener Chaos Expansion and SGD. • WCE transforms stochastic dynamics into a deterministic propagator system. • SGD optimizes the discrepancy functional in the spectral space efficiently. • Maps stochastic inference into a deterministic optimization task. • Numerical validation with growth models and mean-reverting processes.

Keywords:

Stochastic gradient descent

Parameter estimation

Wiener chaos expansion

Geometric Brownian motion

Microbial growth dynamics

Parameter estimation in stochastic differential equations via Wiener chaos expansion and stochastic gradient descent

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