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Found 3 papers, 1 papers with code
Parameter selection in Gaussian process interpolation: an empirical study of selection criteria
This article revisits the fundamental problem of parameter selection for Gaussian process interpolation.
Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation
This article investigates the origin of numerical issues in maximum likelihood parameter estimation for Gaussian process (GP) interpolation and investigates simple but effective strategies for improving commonly used open-source software implementations.
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients
We consider the problem of estimating the parameters of the covariance function of a Gaussian process by cross-validation.
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