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.
arXiv preprint arXiv:2507.11739 , year=
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Fourier Weak SINDy selects orthogonal sinusoidal test functions using multitaper spectral estimation to make weak-form SINDy robust and derivative-free for equation discovery in dynamical systems.
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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.
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Fourier Weak SINDy: Spectral Test Function Selection for Robust Model Identification
Fourier Weak SINDy selects orthogonal sinusoidal test functions using multitaper spectral estimation to make weak-form SINDy robust and derivative-free for equation discovery in dynamical systems.