2 papers
math.ST2025
Adaptive sparse variational approximations for Gaussian process regression
Dennis Nieman, Botond Szabó
Accurate tuning of hyperparameters is crucial to ensure that models can generalise effectively across different settings. In this paper, we present theoretical guarantees for hyper…
math.ST2022
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…