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arXiv · 2007.05074

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

Boumediene Hamzi·Houman Owhadi
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Abstract

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.

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Boumediene Hamzi, Houman Owhadi. 2020-07-09. Learning dynamical systems from data: a simple cross-validation perspective. https://doi.org/10.1016/j.physd.2020.132817

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