Hello, Given an expensive function \boldsymbol{G} :\mathbb{R}^n \xrightarrow{} \mathbb{R}^m whose value is known at samples \boldsymbol{x}^1,\ldots, \boldsymbol{x}^N, I would like to compute the Jacobian and Hessian at each sample or at least at the mean of the samples \overline{\boldsymbol{x}}, …

Smooth delta functions to compute Jacobian and Hessian from samples

mleprovost August 21, 2020, 12:21am 8

If I could afford more evaluations of the function, the best will probably be to use a Smolyak grid to construct an interpolant and then use automatic differentation?

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Smooth delta functions to compute Jacobian and Hessian from samples

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