Neural control of discrete weak formulations: Galerkin, least squares \& minimal-residual methods with quasi-optimal weights (Q2679332)

scientific article; zbMATH DE number 7643972

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English	Neural control of discrete weak formulations: Galerkin, least squares \& minimal-residual methods with quasi-optimal weights	scientific article; zbMATH DE number 7643972

Statements

instance of

scholarly article

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title

Neural control of discrete weak formulations: Galerkin, least squares \& minimal-residual methods with quasi-optimal weights (English)

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author

Ignacio Brevis

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Ignacio Muga

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Kristoffer G. van der Zee

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published in

Computer Methods in Applied Mechanics and Engineering

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publication date

19 January 2023

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full work available at URL

https://arxiv.org/abs/2206.07475

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zbMATH Keywords

optimal neural control

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artificial neural networks

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data-driven discretization

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weighted finite element methods

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quasi-minimization

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quasi-optimal convergence

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describes a project that uses

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Machine Learning and Computational Mathematics

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Identifiers

Mathematics Subject Classification ID

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10.1016/J.CMA.2022.115716

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Sitelinks

Mathematics(1 entry)

mardi Publication:2679332