Archive Files

Volume 11, 2021 / Issue 4

DOI: 10.1615/Int.J.UncertaintyQuantification.v11.i4

Table of Contents:

AN EFFICIENT COMPUTATIONAL METHOD FOR PARAMETER IDENTIFICATION IN THE CONTEXT OF RANDOM SET THEORY VIA BAYESIAN INVERSION Truong-Vinh Hoang, Hermann G. Matthies

Truong-Vinh Hoang
Chair of Mathematics for Uncertainty Quantification, RWTH-Aachen University, Germany; Institute of Scientific Computing, Technische Universität Braunschweig, Germany

Hermann G. Matthies
Institute of Scientific Computing, Technische Universität Braunschweig, Germany

1-18 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2020031869

ERROR CONTROL IN THE NUMERICAL POSTERIOR DISTRIBUTION IN THE BAYESIAN UQ ANALYSIS OF A SEMILINEAR EVOLUTION PDE Maria L. Daza-Torres, J. Cricelio Montesinos-López, Marcos A. Capistrán, J. Andrés Christen, Heikki Haario

Maria L. Daza-Torres
Centro de Investigación en Matemáticas (CIMAT), Guanajuato, GTO, México

J. Cricelio Montesinos-López
Centro de Investigación en Matemáticas (CIMAT), Guanajuato, GTO, México

Marcos A. Capistrán
Centro de Investigación en Matemáticas (CIMAT), Guanajuato, GTO, México

J. Andrés Christen
Centro de Investigación en Matemáticas (CIMAT), Guanajuato, GTO, México

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

19-39 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2020033516

EXPLICIT ESTIMATION OF DERIVATIVES FROM DATA AND DIFFERENTIAL EQUATIONS BY GAUSSIAN PROCESS REGRESSION Hongqiao Wang, Xiang Zhou

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

Xiang Zhou
School of Data Science and Department of Mathematics, City University of Hong Kong, Kowloon, Hong Kong SAR

41-57 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2021034382

ROBUST IMPORTANCE SAMPLING FOR BAYESIAN MODEL CALIBRATION WITH SPATIOTEMPORAL DATA Kyle Neal, Benjamin Schroeder, Joshua Mullins, Abhinav Subramanian, Sankaran Mahadevan

Kyle Neal
Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tennessee 37235, USA

Benjamin Schroeder
V&V, UQ, Credibility Processes Department, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA

Joshua Mullins
V&V, UQ, Credibility Processes Department, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA

Abhinav Subramanian
Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tennessee 37235, USA

Sankaran Mahadevan
Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tennessee 37235, USA

59-80 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2021033499

ACCRUE: ACCURATE AND RELIABLE UNCERTAINTY ESTIMATE IN DETERMINISTIC MODELS Enrico Camporeale, Algo Carè

Enrico Camporeale
University of Colorado, Boulder, Colorado, USA

Algo Carè
University of Brescia, Brescia, Italy

81-94 pages
DOI: 10.1615/Int.J.UncertaintyQuantification.2021034623

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