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Contraction rates for sparse variational approximations in Gaussian process regression
22 September 2021
D. Nieman
Botond Szabó
Harry Van Zanten
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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
21
0
0
04 Apr 2025
Contraction rates for conjugate gradient and Lanczos approximate posteriors in Gaussian process regression
Bernhard Stankewitz
Botond Szabo
18
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
23
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
19
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
38
7
0
14 Oct 2022
Optimal recovery and uncertainty quantification for distributed Gaussian process regression
Amine Hadji
Tammo Hesselink
Botond Szabó
21
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
25
10
0
16 May 2021
Fast Deep Mixtures of Gaussian Process Experts
Clement Etienam
K. Law
S. Wade
Vitaly Zankin
14
1
0
11 Jun 2020
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