Physics-informed boundary integral networks (PIBI-Nets): A data-driven approach for solving partial differential equations-Reference-Cited by-同舟云学术

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Physics-informed boundary integral networks (PIBI-Nets): A data-driven approach for solving partial differential equations

Published:2024-09 Issue: Volume:81 Page:102355
ISSN:1877-7503
Container-title:Journal of Computational Science
language:en
Short-container-title:Journal of Computational Science

Author:

Nagy-Huber Monika^ORCID,Roth Volker

Publisher

Elsevier BV

Reference36 articles.

1. Altitude of the Potentiometric Surface, 2000–15, and Historical Water-Level Changes in the Memphis Aquifer in the Memphis Area, Tennessee;Kingsbury,2018

2. Physics informed neural networks for electromagnetic analysis;Khan;IEEE Trans. Magn.,2022

3. Computational Fluid Dynamics: an Introduction;Anderson,2013

4. Parameter estimation of partial differential equation models;Xun;J. Amer. Statist. Assoc.,2013

5. Deep data assimilation: integrating deep learning with data assimilation;Arcucci;Appl. Sci.,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interpretation of dual time-dependent chloride diffusion in concrete based on Physical Information Neural Networks;Case Studies in Construction Materials;2024-09

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