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Linear-time inference for Gaussian Processes on one dimension
v1v2v3v4v5 (latest)

Linear-time inference for Gaussian Processes on one dimension

11 March 2020
Jackson Loper
David M. Blei
John P. Cunningham
Liam Paninski
ArXiv (abs)PDFHTML

Papers citing "Linear-time inference for Gaussian Processes on one dimension"

16 / 16 papers shown
Title
Exact Gaussian Processes on a Million Data Points
Exact Gaussian Processes on a Million Data Points
Ke Alexander Wang
Geoff Pleiss
Jacob R. Gardner
Stephen Tyree
Kilian Q. Weinberger
A. Wilson
GP
55
230
0
19 Mar 2019
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU
  Acceleration
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob R. Gardner
Geoff Pleiss
D. Bindel
Kilian Q. Weinberger
A. Wilson
GP
136
1,100
0
28 Sep 2018
State Space Gaussian Processes with Non-Gaussian Likelihood
State Space Gaussian Processes with Non-Gaussian Likelihood
H. Nickisch
Arno Solin
A. Grigorevskiy
GP
29
32
0
13 Feb 2018
Multilevel linear models, Gibbs samplers and multigrid decompositions
Multilevel linear models, Gibbs samplers and multigrid decompositions
Giacomo Zanella
Gareth O. Roberts
42
5
0
17 Mar 2017
GPflow: A Gaussian process library using TensorFlow
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
78
666
0
27 Oct 2016
Linear dynamical neural population models through nonlinear embeddings
Linear dynamical neural population models through nonlinear embeddings
Yuanjun Gao
Evan Archer
Liam Paninski
John P. Cunningham
62
155
0
26 May 2016
Preconditioning Kernel Matrices
Preconditioning Kernel Matrices
Kurt Cutajar
Michael A. Osborne
John P. Cunningham
Maurizio Filippone
73
73
0
22 Feb 2016
State Space representation of non-stationary Gaussian Processes
State Space representation of non-stationary Gaussian Processes
A. Benavoli
Marco Zaffalon
GP
36
8
0
07 Jan 2016
Kernel Interpolation for Scalable Structured Gaussian Processes
  (KISS-GP)
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)
A. Wilson
H. Nickisch
GP
69
513
0
03 Mar 2015
Parallel Gaussian Process Regression for Big Data: Low-Rank
  Representation Meets Markov Approximation
Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation
K. H. Low
J. Yu
Jie Chen
Patrick Jaillet
52
52
0
17 Nov 2014
Fast Direct Methods for Gaussian Processes
Fast Direct Methods for Gaussian Processes
Sivaram Ambikasaran
D. Foreman-Mackey
L. Greengard
D. Hogg
M. O’Neil
100
384
0
24 Mar 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
Gaussian Process Kernels for Pattern Discovery and Extrapolation
Gaussian Process Kernels for Pattern Discovery and Extrapolation
A. Wilson
Ryan P. Adams
GP
70
608
0
18 Feb 2013
Laplace approximation for logistic Gaussian process density estimation
  and regression
Laplace approximation for logistic Gaussian process density estimation and regression
J. Riihimaki
Aki Vehtari
49
48
0
01 Nov 2012
Parallel MCMC with Generalized Elliptical Slice Sampling
Parallel MCMC with Generalized Elliptical Slice Sampling
Robert Nishihara
Iain Murray
Ryan P. Adams
107
81
0
28 Oct 2012
Scaling Multidimensional Inference for Structured Gaussian Processes
Scaling Multidimensional Inference for Structured Gaussian Processes
Elad Gilboa
Yunus Saatci
John P. Cunningham
114
61
0
18 Sep 2012
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