A Data-Adaptive Prior for Bayesian Learning of Kernels in Operators

Neil K. Chada, Quanjun Lang, Fei Lu +1

Kernels are efficient in representing nonlocal dependence and they are widely used to design operators between function spaces. Thus, learning kernels in operators from data is an…