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I choose a square exponential kernel ({\tt ExpSquaredKernel} in {\tt george}) $$k(d)=θ_1^2 \exp(\frac{−d^2}{θ_2^2})$$.  In order to choose the hyperparameters $θ_1^2$ and $θ_2^2$ I minimize the objective function: $\chi^2(m) ~*~ \sqrt{\frac{d^2 m}{dt^2} }$ }$, where $m$ is the magnotude, and the fit is done in log time. This works remarkably well in general, with some ``pathological'' exceptions.  \section{Failing fits}