Próximos artigos

Robust Uncertainty Quantification using Response Surface Approximations of Discontinuous Functions Timothy Wildey, Alex Gorodetsky, Anca Belme, John Shadid

Timothy Wildey
Sandia National Labs

Alex Gorodetsky
University of Michigan, Department of Aerospace Engineering

Anca Belme
Sorbonne Universite, CNRS

John Shadid
Sandia National Laboratories

DOI: 10.1615/Int.J.UncertaintyQuantification.2019026974

Bayesian Optimal Experimental Design Involving Multiple Setups for Dynamic Structural Testing Sahil Bansal

Sahil Bansal
Indian Institute of Technology Delhi

DOI: 10.1615/Int.J.UncertaintyQuantification.2019025897

Wasserstein metric-driven Bayesian inversion with applications to signal processing Mohammad Motamed, Daniel Appelo

Mohammad Motamed
University of New Mexico

Daniel Appelo
University of Colorado, Boulder

DOI: 10.1615/Int.J.UncertaintyQuantification.2019027745

Embedded Model Error Representation for Bayesian Model Calibration Khachik Sargsyan, Xun Huan, Habib N. Najm

Khachik Sargsyan
Sandia National Laboratories

Xun Huan
University of Michigan, Ann Arbor

Habib N. Najm
Sandia National Laboratories

DOI: 10.1615/Int.J.UncertaintyQuantification.2019027384

Surrogate Modeling of Stochastic Functions - Application to computational Electromagnetic Dosimetry soumaya azzi, Yuanyuan Huang, Bruno Sudret, Joe Wiart

soumaya azzi
Télécom Paristech

Yuanyuan Huang
Télécom Paristech

Bruno Sudret
ETH Zurich, Institute of Structural Engineering, Chair of Risk, Safety and Uncertainty Quantification, Stefano-Franscini-Platz 5, CH-8093 Zurich, Switzerland

Joe Wiart
Télécom Paristech

DOI: 10.1615/Int.J.UncertaintyQuantification.2019029103

PIG Process: Joint Modeling of Point and Integral Responses in Computer Experiments Heng Su, Rui Tuo, Jeff Wu

Heng Su
Wells Fargo Bank

Rui Tuo
Texas A&M University

Jeff Wu
Georgia Institute of Technology

DOI: 10.1615/Int.J.UncertaintyQuantification.2019027823

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