Sparse Identification of Nonlinear Dynamics ( SINDy): Sparse Machine Learning Models 5 Years Later

Machine learning is enabling the discovery of dynamical systems models and governing equations purely from measurement data. Five years after the original SINDy paper, we revisit this topic, describing the algorithm and exploring the main challenges for computing sparse nonlinear models from data. This is part of a multipart series. Original SINDy paper: SINDy for PDEs: Joint work with Nathan Kutz: eigensteve on Twitter