OpenAlex | Parsimony as the ultimate regularizer for physics-informed machine learning

Parsimony as the ultimate regularizer for physics-informed machine learning

Work

Year: 2022

Type: article

Source: Nonlinear Dynamics

Authors J. Nathan Kutz, Steven L. Brunton

Institutions University of Washington Applied Physics Laboratory, University of Washington

Cites: 103

Cited by: 41

Related to: 10

FWCI: 5.21

Citation percentile (by year/subfield): 99.98

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: closed

Funder Air Force Office of Scientific Research

Grant ID FA9550-19-1-0386