Stochastic reduced order models for inverse problems under uncertainty

DOI10.1016/j.cma.2014.11.021zbMath1425.65068OpenAlexW2017247230WikidataQ34797667 ScholiaQ34797667MaRDI QIDQ1798577

Mircea D. Grigoriu, Wilkins Aquino, James E. Warner

Publication date: 23 October 2018

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4281272

zbMATH Keywords

stochastic optimizationuncertainty quantificationstochastic inverse problemsmaterial identificationstochastic reduced order models

Mathematics Subject Classification ID

Related Items (7)

A variational inequality based stochastic approximation for estimating the flexural rigidity in random fourth-order models ⋮ Generalized Bayes approach to inverse problems with model misspecification ⋮ VI-DGP: a variational inference method with deep generative prior for solving high-dimensional inverse problems ⋮ Estimates of System Response Maxima by Extreme Value Theory and Surrogate Models ⋮ A marginalized unscented Kalman filter for efficient parameter estimation with applications to finite element models ⋮ Stochastic reduced-order models for stable nonlinear ordinary differential equations ⋮ A Convex Optimization Framework for the Inverse Problem of Identifying a Random Parameter in a Stochastic Partial Differential Equation

Uses Software

• Matlab

Cites Work

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