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Volume 11, 2021 / Issue 2

- IN PROGRESS

Table of Contents:

COMPUTATION OF SOBOL INDICES IN GLOBAL SENSITIVITY ANALYSIS FROM SMALL DATA SETS BY PROBABILISTIC LEARNING ON MANIFOLDS Maarten Arnst, Christian Soize, Kevin Bulthuis

Maarten Arnst
University de Liege, Departement d'Aerospatiale et Mecanique, B-4000 Liege, Belgium

Christian Soize
Modélisation et Simulation Multi-Echelle, Université Paris-Est Marne-la-Vallée, MSME UMR 8208 CNRS, Marne-la-Vallée, France

Kevin Bulthuis
Aérospatiale et Mécanique, Université de Liège, Liège, Belgium

1-23 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2020032674

STOCHASTIC SPECTRAL EMBEDDING Stefano Marelli, P.-R. Wagner, Christos Lataniotis, Bruno Sudret

Stefano Marelli
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland

P.-R. Wagner
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Switzerland

Christos Lataniotis
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland

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

25-47 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2020034395

PARAMETER ESTIMATION OF STOCHASTIC CHAOTIC SYSTEMS Ramona Maraia, Sebastian Springer, Heikki Haario, Janne Hakkarainen, Eero Saksman

Ramona Maraia
Department of Computational Engineering, Lappeenranta University of Technology, Lappeenranta, 53850, Finland

Sebastian Springer
Department of Computational Engineering, Lappeenranta University of Technology, Lappeenranta, 53850, Finland

Heikki Haario
Department of Computational Engineering, Lappeenranta University of Technology, Lappeenranta, 53850, Finland; Earth Observation Research, Finnish Meteorological Institute, Helsinki, 00560, Finland

Janne Hakkarainen
Earth Observation Research, Finnish Meteorological Institute, Helsinki, 00560, Finland

Eero Saksman
Department of Mathematics and Statistics, University of Helsinki, 00560, Finland

49-62 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2020032807

DEEP LEARNING OF PARAMETERIZED EQUATIONS WITH APPLICATIONS TO UNCERTAINTY QUANTIFICATION Tong Qin, Zhen Chen, John D. Jakeman, Dongbin Xiu

Tong Qin
Department of Mathematics, University of Michigan, Ann Arbor, Michigan 48109, USA

Zhen Chen
Department of Mathematics, The Ohio State University, Columbus, Ohio 43210, USA

John D. Jakeman
Optimization and Uncertainty Quantification, Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87123, USA

Dongbin Xiu
Ohio Eminent Scholar Department of Mathematics The Ohio State University Columbus, Ohio 43210, USA

63-82 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2020034123

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