61 citations · 166 across the 16 of their papers we have counts for
23 papers
Linear methods for non-linear inverse problems
Geerten Koers, Botond Szabo, Aad van der Vaart
We consider the recovery of an unknown function from a noisy observation of the solution to a partial differential equation that can be written in the form $\mathcal{L} u…
Adaptation using spatially distributed Gaussian Processes
Botond Szabo, Amine Hadji, Aad van der Vaart
We consider the accuracy of an approximate posterior distribution in nonparametric regression problems by combining posterior distributions computed on subsets of the data defined…
Variational Gaussian Processes For Linear Inverse Problems
Thibault Randrianarisoa, Botond Szabo
By now Bayesian methods are routinely used in practice for solving inverse problems. In inverse problems the parameter or signal of interest is observed only indirectly, as an imag…
Skewed Bernstein-von Mises theorem and skew-modal approximations
Daniele Durante, Francesco Pozza, Botond Szabo
Gaussian approximations are routinely employed in Bayesian statistics to ease inference when the target posterior is intractable. Although these approximations are asymptotically j…
Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression
Dennis Nieman, Botond Szabo, Harry van Zanten
We investigate the frequentist guarantees of the variational sparse Gaussian process regression model. In the theoretical analysis, we focus on the variational approach with spectr…
Contraction rates for sparse variational approximations in Gaussian process regression
Dennis Nieman, Botond Szabo, Harry van Zanten
We study the theoretical properties of a variational Bayes method in the Gaussian Process regression model. We consider the inducing variables method introduced by Titsias (2009a)…