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Configurable kernel functions used to define the structural properties and smoothness of latent functions in Gaussian processes.
Distinct from Kernel Configuration Utilities: Distinct from Kernel Configuration Utilities: focuses on statistical modeling kernels for Gaussian processes rather than system-level kernel drivers.
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Specifies model generalization properties by selecting covariance functions to define function space behavior.