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

07/09/2020

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by   Boumediene Hamzi, et al.

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16

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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 <cit.> and its variants based on Maximum Mean Discrepancy and Lyapunov exponents) as simple approaches for learning the kernel used in these emulators.