A General Theory for Constructing Compactly Supported Basis Functions for Gaussian Processes Driven by Stochastic Differential Equations

Kernel packets (KPs) provide a general framework to construct compactly supported basis functions for Gaussian processes (GPs) driven by stochastic differential equations (SDEs), enabling efficient training and prediction of GP models.