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Pointwise uncertainty quantification for sparse variational Gaussian
  process regression with a Brownian motion prior

Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior

29 September 2023
Luke Travis
Kolyan Ray
ArXivPDFHTML

Papers citing "Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior"

4 / 4 papers shown
Title
A variational Bayes approach to debiased inference for low-dimensional
  parameters in high-dimensional linear regression
A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression
Ismaël Castillo
Alice L'Huillier
Kolyan Ray
Luke Travis
34
0
0
18 Jun 2024
Smoothness Estimation for Whittle-Matérn Processes on Closed
  Riemannian Manifolds
Smoothness Estimation for Whittle-Matérn Processes on Closed Riemannian Manifolds
Moritz Korte-Stapff
Toni Karvonen
Eric Moulines
16
0
0
31 Dec 2023
Variational Gaussian Processes For Linear Inverse Problems
Variational Gaussian Processes For Linear Inverse Problems
Thibault Randrianarisoa
Botond Szabó
31
3
0
01 Nov 2023
Contraction rates for sparse variational approximations in Gaussian
  process regression
Contraction rates for sparse variational approximations in Gaussian process regression
D. Nieman
Botond Szabó
Harry Van Zanten
41
17
0
22 Sep 2021
1