Statistical inverse identification for nonlinear train dynamics using a surrogate model in a Bayesian framework

Author:

Lebel D.,Soize C.,Fünfschilling C.,Perrin G.

Funder

SNCF

Publisher

Elsevier BV

Subject

Mechanical Engineering,Mechanics of Materials,Acoustics and Ultrasonics,Condensed Matter Physics

Reference25 articles.

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

2. Identification of bayesian posteriors for coefficients of chaos expansions;Arnst;J. Comput. Phys.,2010

3. Surrogate and Reduced-Order Modeling: A Comparison of Approaches for Large-Scale Statistical Inverse Problems;Frangos,2010

4. Spectral likelihood expansions for Bayesian inference;Nagel;J. Comput. Phys.,2016

5. Computational Statistics;Givens,2013

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