  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.
