Contraction rates for sparse variational approximations in Gaussian process regression

22 September 2021

Papers citing "Contraction rates for sparse variational approximations in Gaussian process regression"

16 / 16 papers shown

Title
Adaptive sparse variational approximations for Gaussian process regression Dennis Nieman Botond Szabó 23 0 0 04 Apr 2025
Contraction rates for conjugate gradient and Lanczos approximate posteriors in Gaussian process regression Bernhard Stankewitz Botond Szabo 20 2 0 18 Jun 2024
Further Understanding of a Local Gaussian Process Approximation: Characterising Convergence in the Finite Regime Anthony Stephenson Robert Allison Edward O. Pyzer-Knapp 16 0 0 09 Apr 2024
On Uncertainty Quantification for Near-Bayes Optimal Algorithms Ziyu Wang Chris Holmes UQCV 27 2 0 28 Mar 2024
Adaptation using spatially distributed Gaussian Processes Botond Szabó Amine Hadji A. van der Vaart 25 2 0 21 Dec 2023
Variational Gaussian Processes For Linear Inverse Problems Thibault Randrianarisoa Botond Szabó 26 3 0 01 Nov 2023
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior Luke Travis Kolyan Ray 16 4 0 29 Sep 2023
Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression D. Nieman Botond Szabó Harry Van Zanten 18 5 0 21 Dec 2022
Variational Inference for Semiparametric Bayesian Novelty Detection in Large Datasets L. Benedetti Eric Boniardi Leonardo Chiani Jacopo Ghirri Marta Mastropietro A. Cappozzo Francesco Denti 19 0 0 04 Dec 2022
Scalable and adaptive variational Bayes methods for Hawkes processes Déborah Sulem Vincent Rivoirard Judith Rousseau 21 0 0 01 Dec 2022
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees Alexander Terenin David R. Burt A. Artemev Seth Flaxman Mark van der Wilk C. Rasmussen Hong Ge 40 7 0 14 Oct 2022
Optimal recovery and uncertainty quantification for distributed Gaussian process regression Amine Hadji Tammo Hesselink Botond Szabó 23 3 0 06 May 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 14 18 0 08 Feb 2022
Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes Veit Wild Motonobu Kanagawa Dino Sejdinovic 22 16 0 02 Jun 2021
Posterior contraction for deep Gaussian process priors G. Finocchio Johannes Schmidt-Hieber 27 10 0 16 May 2021
Fast Deep Mixtures of Gaussian Process Experts Clement Etienam K. Law S. Wade Vitaly Zankin 19 1 0 11 Jun 2020