Multi-output local Gaussian process regression: applications to uncertainty quantification
type: Item
instance of: scholarly article
title: Multi-output local Gaussian process regression: applications to uncertainty quantification
zbMATH Open document ID: 1277.60066
author: I. Bilionis
author: Nicholas Zabaras
published in: Journal of Computational Physics
publication date: 2013-12-12T00:00:00Z
Mathematics Subject Classification ID: 60G15
Mathematics Subject Classification ID: 60H35
Mathematics Subject Classification ID: 60H10
zbMATH DE Number: 6237752
zbMATH Keywords: Gaussian process
zbMATH Keywords: Bayesian
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: stochastic partial differential equations
zbMATH Keywords: multi-output
zbMATH Keywords: multi-element
zbMATH Keywords: adaptivity
describes a project that uses: dynaTree
describes a project that uses: Trilinos
describes a project that uses: GSL
MaRDI profile type: Publication
full work available at URL: j.jcp.2012.04.047
OpenAlex ID: W2060682310
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DOI: 10.1016/J.JCP.2012.04.047
description: scientific article; zbMATH DE number 6237752