= Gaussian process approximations
{wiki=Gaussian_process_approximations}
Gaussian process (GP) approximation is a powerful statistical technique utilized primarily in the context of machine learning and Bayesian statistics for function approximation, regression, and optimization. A Gaussian process is a collection of random variables, any finite number of which have a joint Gaussian distribution. It is particularly appealing due to its flexibility in modeling complex functions and the uncertainty associated with them.
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