Numerically Stable Sparse Gaussian Processes via Minimum Separation
using Cover Trees

Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees

14 October 2022

Alexander Terenin

Seth Flaxman

Mark van der Wilk

Papers citing "Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees"

19 / 19 papers shown

Title
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 53 20 0 05 Nov 2021
Contraction rates for sparse variational approximations in Gaussian process regression D. Nieman Botond Szabó Harry Van Zanten 86 17 0 22 Sep 2021
Adaptive Inducing Points Selection For Gaussian Processes Théo Galy-Fajou Manfred Opper 60 16 0 21 Jul 2021
Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation S. Basak S. Petit Julien Bect E. Vázquez 35 14 0 24 Jan 2021
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 49 60 0 08 Nov 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression David R. Burt C. Rasmussen Mark van der Wilk 66 74 0 01 Aug 2020
Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 48 164 0 21 Feb 2020
Rates of Convergence for Sparse Variational Gaussian Process Regression David R. Burt C. Rasmussen Mark van der Wilk 47 153 0 08 Mar 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era N. Durrande Vincent Adam L. Bordeaux Stefanos Eleftheriadis J. Hensman 23 26 0 26 Feb 2019
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob R. Gardner Geoff Pleiss D. Bindel Kilian Q. Weinberger A. Wilson GP 113 1,095 0 28 Sep 2018
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 123 342 0 06 Jul 2018
Fully Scalable Gaussian Processes using Subspace Inducing Inputs A. Panos P. Dellaportas Michalis K. Titsias 39 12 0 06 Jul 2018
Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features Jean-François Ton Seth Flaxman Dino Sejdinovic Samir Bhatt GP 58 53 0 15 Nov 2017
A general framework for Vecchia approximations of Gaussian processes Matthias Katzfuss J. Guinness 42 258 0 21 Aug 2017
GPflow: A Gaussian process library using TensorFlow A. G. Matthews Mark van der Wilk T. Nickson Keisuke Fujii A. Boukouvalas Pablo León-Villagrá Zoubin Ghahramani J. Hensman GP 73 664 0 27 Oct 2016
A multi-resolution approximation for massive spatial datasets Matthias Katzfuss 68 243 0 16 Jul 2015
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes A. G. Matthews J. Hensman Richard Turner Zoubin Ghahramani 76 192 0 27 Apr 2015
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 101 1,230 0 26 Sep 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 325 7,923 0 13 Jun 2012

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