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Learning dynamical systems from data: a simple cross-validation perspective
Boumediene Hamzi, Houman Owhadi · 2020-07-10 · via cs.LG updates on arXiv.org

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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