Archive Files

Volume 12, 2022 / Edição 4

DOI: 10.1615/Int.J.UncertaintyQuantification.v12.i4

Table of Contents:

MULTILEVEL QUASI-MONTE CARLO FOR INTERVAL ANALYSIS Robin R.P. Callens, Matthias Faess, David Moens

Robin R.P. Callens
KU Leuven Department of Mechanical Engineering Division LMSD, Sint-Katelijne-Waver, Antwerp, 2860, Belgium

Matthias Faess
TU Dortmund

David Moens
KU Leuven Department of Mechanical Engineering Division LMSD, Sint-Katelijne-Waver, Antwerp, 2860, Belgium

1-19 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2022039245

CONTROL VARIATES WITH A DIMENSION REDUCED BAYESIAN MONTE CARLO SAMPLER Xin Cai, Junda Xiong, Hongqiao Wang, Jinglai Li

Xin Cai
School of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China

Junda Xiong
School of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China

Hongqiao Wang
School of Mathematics and Statistics, Central South University, Changsha 410083, China

Jinglai Li
School of Mathematics, University of Birmingham, Birmingham B15 2TT, United Kingdom

21-37 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2022035744

MANIFOLD LEARNING-BASED POLYNOMIAL CHAOS EXPANSIONS FOR HIGH-DIMENSIONAL SURROGATE MODELS Katiana Kontolati, Dimitrios Loukrezis, Ketson R. M. dos Santos, Dimitrios G. Giovanis, Michael D. Shields

Katiana Kontolati
Department of Civil & Systems Engineering, Johns Hopkins University, Baltimore, Maryland, USA

Dimitrios Loukrezis
Institute for Accelerator Science and Electromagnetic Fields, Technische Universität Darmstadt, Darmstadt, Germany; Centre for Computational Engineering, Technische Universität Darmstadt, Darmstadt, Germany

Ketson R. M. dos Santos
Earthquake Engineering and Structural Dynamics Laboratory, École Polytechnique Fédérale de Lausanne, VD, Switzerland

Dimitrios G. Giovanis
Department of Civil & Systems Engineering, Johns Hopkins University, Baltimore, Maryland, USA

Michael D. Shields
Department of Civil & Systems Engineering, Johns Hopkins University, Baltimore, Maryland, USA

39-64 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2022039936

L^p CONVERGENCE OF APPROXIMATE MAPS AND PROBABILITY DENSITIES FOR FORWARD AND INVERSE PROBLEMS IN UNCERTAINTY QUANTIFICATION Troy Butler, Timothy Wildey, W. Zhang

Troy Butler
University of Colorado Denver, Department of Mathematical and Statistical Sciences, Denver, Colorado 80204, USA

Timothy Wildey
Optimization and Uncertainty Quantification Department, Center for Computing Research, Sandia National Laboratories, Albuquerque, NM 87185

W. Zhang
University of Colorado Denver, Department of Mathematical and Statistical Sciences, Denver, Colorado 80204, USA

65-92 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2022038086

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