When does a Gaussian process have its paths in a reproducing kernel Hilbert space?

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Authors: Ingo Steinwart
Cited by: 0

Abstract

We investigate for which Gaussian processes there do or do not exist reproducing kernel Hilbert spaces (RKHSs) that contain almost all of their paths. In particular, we establish a new result that makes it possible to exclude the existence of such RKHSs in many cases. Moreover, we combine this negative result with some known techniques to establish positive results. Here it turns out that for many classical families of Gaussian processes we can fully characterize for which members of these families there exist RKHSs containing the paths. Similar characterizations are obtained for Gaussian processes, for which the RKHSs of their covariance functions are Sobolev spaces or Sobolev spaces of mixed smoothness.

Fields of Study & Subjects

Gaussian Processes and Bayesian Inference

Publication details

Journal / source
Transactions of the American Mathematical Society
Publication date
14 July 2026
Language
EN