Generative modeling of Sparse Approximate Inverse Preconditioners

Li, M., Wang, H. and Jimack, P. orcid.org/0000-0001-9463-7595 (2024) Generative modeling of Sparse Approximate Inverse Preconditioners. In: Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part III. International Conference on Computational Science (ICCS), 02-04 Jul 2024, Málaga. Springer , Berlin, Heidelberg , pp. 378-392. ISBN 978-3-031-63758-2

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Item Type: Proceedings Paper
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© Author | ACM 2024. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part III, https://doi.org/10.1007/978-3-031-63759-9_40

Keywords: Deep learning, Sparse matrices, Preconditioning, Elliptic partial differential equations, Finite element methods
Dates:
  • Published: 23 July 2024
  • Published (online): 2 July 2024
  • Accepted: 3 April 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Computation Science & Engineering
Depositing User: Symplectic Publications
Date Deposited: 29 Apr 2024 10:13
Last Modified: 26 Jul 2024 14:57
Published Version: https://dl.acm.org/doi/10.1007/978-3-031-63759-9_4...
Status: Published
Publisher: Springer
Identification Number: 10.1007/978-3-031-63759-9_40
Open Archives Initiative ID (OAI ID):

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