A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations
type: Item
instance of: scholarly article
title: A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations
author: Ignacio Brevis
author: Ignacio Muga
author: K. G. van der Zee
publication date: 2021-06-23T00:00:00Z
full work available at URL: https://nottingham-repository.worktribe.com/output/4894782
Mathematics Subject Classification ID: 65N30
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 65N15
Mathematics Subject Classification ID: 65N50
Mathematics Subject Classification ID: 65M60
zbMATH DE Number: 7362360
zbMATH Keywords: goal-oriented finite elements
zbMATH Keywords: machine-learning acceleration
zbMATH Keywords: residual minimization
zbMATH Keywords: Petrov-Galerkin method
zbMATH Keywords: weighted inner-products
zbMATH Keywords: data-driven algorithms
describes a project that uses: Loewner
MaRDI profile type: Publication
OpenAlex ID: W3083770698
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DOI: 10.1016/J.CAMWA.2020.08.012
published in: Computers & Mathematics with Applications
description: scientific article; zbMATH DE number 7362360