Learning model discrepancy: A Gaussian process and sampling-based approach

Gardner, P. orcid.org/0000-0002-1882-9728, Rogers, T.J. orcid.org/0000-0002-3433-3247, Lord, C. orcid.org/0000-0002-2470-098X et al. (1 more author) (2021) Learning model discrepancy: A Gaussian process and sampling-based approach. Mechanical Systems and Signal Processing, 152. 107381. ISSN 0888-3270

Abstract

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Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Keywords: Model discrepancy; Gaussian process regression; Importance sampling; Bayesian history matching
Dates:
  • Accepted: 23 October 2020
  • Published (online): 10 December 2020
  • Published: May 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
Funder
Grant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/N010884/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/R006768/1
Depositing User: Symplectic Sheffield
Date Deposited: 21 Jan 2021 15:49
Last Modified: 21 Jan 2021 15:49
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.ymssp.2020.107381
Open Archives Initiative ID (OAI ID):

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