Implementation of a GP
Felipe Tobar
2021 Talk
in
Tutorial: The Art of Gaussian Processes: Classical and Contemporary
in
Tutorial: The Art of Gaussian Processes: Classical and Contemporary
Abstract
We show how to implement a vanilla GP from scratch, we refer to the particulars of coding the kernel, the likelihood function and the train() function. We apply this minimal GP toolbox to a couple of datasets to illustrate the GP’s ease of use and modelling abilities
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