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.Comment: 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_perspectiv
