Multi-scale physics-informed machine learning using the Buckingham Pi theorem-Reference-Cited by-同舟云学术

Multi-scale physics-informed machine learning using the Buckingham Pi theorem

Published:2023-02 Issue: Volume:474 Page:111810
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Oppenheimer Michael W.,Doman David B.,Merrick Justin D.

Publisher

Elsevier BV

Subject

Computer Science Applications,Physics and Astronomy (miscellaneous),Applied Mathematics,Computational Mathematics,Modeling and Simulation,Numerical Analysis

Reference16 articles.

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3. Physics-informed machine learning;Karniadakis;Nat. Rev. Phys.,2021

4. How neural networks extrapolate: from feedforward to graph neural networks;Xu,2021

5. The Physical Basis of Dimensional Analysis;Sonin,2001

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