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Rates of Convergence for Sparse Variational Gaussian Process Regression
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Rates of Convergence for Sparse Variational Gaussian Process Regression

David R. Burt
C. Rasmussen
Mark van der Wilk
ArXiv (abs)PDFHTML

Papers citing "Rates of Convergence for Sparse Variational Gaussian Process Regression"

12 / 12 papers shown
Title
Verification and Validation for Trustworthy Scientific Machine Learning
Verification and Validation for Trustworthy Scientific Machine Learning
John D. Jakeman
Lorena A. Barba
J. Martins
Thomas O'Leary-Roseberry
AI4CE
120
0
0
21 Feb 2025
Exact sampling of determinantal point processes with sublinear time preprocessing
Exact sampling of determinantal point processes with sublinear time preprocessing
Michal Derezinski
Daniele Calandriello
Michal Valko
56
55
0
31 May 2019
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees
Jonathan H. Huggins
Trevor Campbell
Mikolaj Kasprzak
Tamara Broderick
62
15
0
26 Jun 2018
Variational Fourier features for Gaussian processes
Variational Fourier features for Gaussian processes
J. Hensman
N. Durrande
Arno Solin
VLM
68
200
0
21 Nov 2016
Exact Sampling from Determinantal Point Processes
Exact Sampling from Determinantal Point Processes
Philipp Hennig
Roman Garnett
52
18
0
22 Sep 2016
Understanding Probabilistic Sparse Gaussian Process Approximations
Understanding Probabilistic Sparse Gaussian Process Approximations
Matthias Bauer
Mark van der Wilk
C. Rasmussen
52
259
0
15 Jun 2016
Fast DPP Sampling for Nyström with Application to Kernel Methods
Fast DPP Sampling for Nyström with Application to Kernel Methods
Chengtao Li
Stefanie Jegelka
S. Sra
48
76
0
19 Mar 2016
Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes
Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes
Nima Anari
S. Gharan
A. Rezaei
49
130
0
16 Feb 2016
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes
A. G. Matthews
J. Hensman
Richard Turner
Zoubin Ghahramani
81
192
0
27 Apr 2015
Scalable Variational Gaussian Process Classification
Scalable Variational Gaussian Process Classification
J. Hensman
A. G. Matthews
Zoubin Ghahramani
BDL
75
645
0
07 Nov 2014
Gaussian Processes for Big Data
Gaussian Processes for Big Data
J. Hensman
Nicolò Fusi
Neil D. Lawrence
GP
107
1,232
0
26 Sep 2013
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning
Alex Gittens
Michael W. Mahoney
118
415
0
07 Mar 2013

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