Stochastic reduced order models for inverse problems under uncertainty-Reference-Cited by-同舟云学术

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Stochastic reduced order models for inverse problems under uncertainty

Published:2015-03 Issue: Volume:285 Page:488-514
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

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

Funder

Sandia National Laboratories

National Institutes of Health

Publisher

Elsevier BV

Subject

Computer Science Applications,General Physics and Astronomy,Mechanical Engineering,Mechanics of Materials,Computational Mechanics

Reference28 articles.

1. A novel Bayesian strategy for the identification of spatially varying material properties and model validation: an application to static elastography;Koutsourelakis;Internat. J. Numer. Methods Engrg.,2012

2. A Bayesian approach to the inverse heat conduction problem;Wang;Int. J. Heat Mass Transfer,2004

3. A stochastic collocation approach to Bayesian inference in inverse problems;Marzouk;Commun. Comput. Phys.,2009

4. An efficient Bayesian inference approach to inverse problems based on an adaptive sparse grid collocation method;Ma;Inverse Problems,2009

5. Stochastic inverse heat conduction using a spectral approach;Narayanan;Internat. J. Numer. Methods Engrg.,2004

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