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arXiv:2007.05074 [cs.LG]AbstractReferencesReviewsResources

Learning dynamical systems from data: a simple cross-validation perspective

Boumediene Hamzi, Houman Owhadi

Published 2020-07-09Version 1

Regressing the vector field of a dynamical system from a finite number of observed states is a natural way to learn surrogate models for such systems. We present variants of cross-validation (Kernel Flows \cite{Owhadi19} and its variants based on Maximum Mean Discrepancy and Lyapunov exponents) as simple approaches for learning the kernel used in these emulators.

Comments: File uploaded on arxiv on Sunday, July 5th, 2020. Got delayed due to tex problems on ArXiv. Original version at https://www.researchgate.net/publication/342693818_Learning_dynamical_systems_from_data_a_simple_cross-validation_perspective
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