SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations-Reference-Cited by-同舟云学术

SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations

Published:2021-03 Issue: Volume:428 Page:109962
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Zhang Sheng^ORCID,Lin Guang^ORCID

Funder

Brookhaven National Laboratory

Army Research Office

National Science Foundation

U.S. Department of Energy

Publisher

Elsevier BV

Subject

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

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