International Journal for Uncertainty Quantification
Latest Publications

TOTAL DOCUMENTS

333

(FIVE YEARS 106)

H-INDEX

25

(FIVE YEARS 3)

Published By Begell House Inc.

2152-5080

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Stable Likelihood Computation for Machine Learning of Linear Differential Operators with Gaussian Processes

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2022038966 ◽

2022 ◽

Author(s):

Omid Chatrabgoun ◽

Mohsen Esmaeilbeigi ◽

Meisam Cheraghi ◽

Alireza Daneshkhah

Keyword(s):

Machine Learning ◽

Gaussian Processes ◽

Differential Operators ◽

Linear Differential Operators ◽

Linear Differential

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Multilevel Quasi-Monte Carlo For Interval Analysis

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2022039245 ◽

2022 ◽

Author(s):

Robin Callens ◽

Matthias Faes ◽

David Moens

Keyword(s):

Monte Carlo ◽

Interval Analysis ◽

Quasi Monte Carlo

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Statistical closure modeling for reduced-order models of stationary systems by the ROMES method

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021035961 ◽

2021 ◽

Author(s):

Stefano Pagani ◽

Andrea Manzoni ◽

Kevin Carlberg

Keyword(s):

Reduced Order Models ◽

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SPARSE TENSOR PRODUCT APPROXIMATION FOR A CLASS OF GENERALIZED METHOD OF MOMENTS ESTIMATORS

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021037549 ◽

2021 ◽

Author(s):

Alexandros Gilch ◽

Michael Griebel ◽

Jens Oettershagen

Keyword(s):

Tensor Product ◽

Method Of Moments ◽

Generalized Method Of Moments ◽

Tensor Product Approximation ◽

Moments Estimators

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Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021036153 ◽

2021 ◽

Author(s):

Nora Lüthen ◽

Stefano Marelli ◽

Bruno Sudret

Keyword(s):

Polynomial Chaos ◽

Engineering Applications ◽

Sparse Polynomial ◽

Automatic Selection ◽

Polynomial Chaos Expansions ◽

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A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021035621 ◽

2021 ◽

Author(s):

Raphaël Gautier ◽

Piyush Pandita ◽

Sayan Ghosh ◽

Dimitri Mavris

Keyword(s):

Dimension Reduction ◽

Gaussian Processes ◽

Reduction Method ◽

Dimension Reduction Method ◽

Supervised Dimension Reduction ◽

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Sparse Gaussian process model with mixed covariance function for uncertainty quantification

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021035851 ◽

2021 ◽

Author(s):

kai cheng ◽

Zhenzhou Lu ◽

Sinan Xiao ◽

Sergey Oladyshkin ◽

Wolfgang Nowak

Keyword(s):

Gaussian Process ◽

Uncertainty Quantification ◽

Process Model ◽

Covariance Function ◽

Gaussian Process Model

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Local Voronoi tessellations for robust multi-wave calibration of computer models

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021034779 ◽

2021 ◽

Author(s):

Wenzhe Xu ◽

Daniel Williamson ◽

Peter Challenor

Keyword(s):

Computer Models ◽

Voronoi Tessellations

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Mean-field control variate methods for kinetic equations with uncertainties and applications to socio-economic sciences

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021037960 ◽

2021 ◽

Author(s):

Lorenzo Pareschi ◽

Torsten Trimborn ◽

Mattia Zanella

Keyword(s):

Kinetic Equations ◽

Control Variate ◽

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FOREWORD: SPECIAL ISSUE ON MULTILEVEL-MULTIFIDELITY APPROACHES FOR UNCERTAINTY QUANTIFICATION

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.v11.i1.10 ◽

2021 ◽

Vol 11 (1) ◽

pp. v-ix

Author(s):

Michael S. Eldred ◽

Gianluca Geraci ◽

Gianluca Iaccarino

Keyword(s):

Uncertainty Quantification ◽

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