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math.NA2023
Gaussian Process Regression under Computational and Epistemic Misspecification
Daniel Sanz-Alonso, Ruiyi Yang
Gaussian process regression is a classical kernel method for function estimation and data interpolation. In large data applications, computational costs can be reduced using low-ra…
math.NA2019★ 4 cited
Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
John Harlim, Daniel Sanz-Alonso, Ruiyi Yang
This paper investigates the formulation and implementation of Bayesian inverse problems to learn input parameters of partial differential equations (PDEs) defined on manifolds. Spe…