PDE-LEARN: Using deep learning to discover partial differential equations from noisy, limited data-Reference-Cited by-同舟云学术

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PDE-LEARN: Using deep learning to discover partial differential equations from noisy, limited data

Published:2024-06 Issue: Volume:174 Page:106242
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Stephany Robert^ORCID,Earls Christopher

Funder

Office of Naval Research

Publisher

Elsevier BV

Reference41 articles.

1. Mortality causes universal changes in microbial community composition;Abreu;Nature Communications,2019

2. A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening;Allen;Acta Metallurgica,1979

3. Transient invaders can induce shifts between alternative stable states of microbial communities;Amor;Science Advances,2020

4. Data-driven discovery of free-form governing differential equations;Atkinson,2019

5. Spectral and finite difference solutions of the Burgers equation;Basdevant;Computers & Fluids,1986

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1. An immersed boundary fast meshfree integration methodology with consistent weight learning;Computer Methods in Applied Mechanics and Engineering;2024-09

2. Learning unbounded-domain spatiotemporal differential equations using adaptive spectral methods;Journal of Applied Mathematics and Computing;2024-06-03

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