Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs

Florido, J., Wang, H., Khan, A. et al. (1 more author) (2024) Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs. In: Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part III. International Conference on Computational Science (ICCS) 2024: 24th International Conference, 02-04 Jul 2024, Málaga. Springer , Berlin, Heidelberg , pp. 323-337. 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_36.

Keywords: Partial differential equations, Deep learning, Physics-informed neural networks, Adaptivity
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 09:55
Last Modified: 26 Jul 2024 14:33
Published Version: https://dl.acm.org/doi/abs/10.1007/978-3-031-63759...
Status: Published
Publisher: Springer
Identification Number: 10.1007/978-3-031-63759-9_36
Open Archives Initiative ID (OAI ID):

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