An active learning method based on E-SINDy identifies governing ODEs and PDEs accurately with significantly fewer data samples than random sampling across tested systems.
Extracting structured dynamical sys- tems using sparse optimization with very few samples.Multiscale Modeling & Simulation, 18(4):1435– 1461, 2020
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How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit
An active learning method based on E-SINDy identifies governing ODEs and PDEs accurately with significantly fewer data samples than random sampling across tested systems.