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PSI-SINDy: Post-Selection Inference for Sparse Identification of Nonlinear Dynamics
Sparse identification of nonlinear dynamics (SINDy) is a data-driven framework for discovering governing dynamics from time-series data by identifying a sparse subset of candidate dynamical terms from a prespecified library. In this work, we develop a statistical inference framework for quantifying
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