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Variational Fourier features for Gaussian processes
v1v2 (latest)

Variational Fourier features for Gaussian processes

21 November 2016
J. Hensman
N. Durrande
Arno Solin
    VLM
ArXiv (abs)PDFHTML

Papers citing "Variational Fourier features for Gaussian processes"

50 / 138 papers shown
Title
Periodic Activation Functions Induce Stationarity
Periodic Activation Functions Induce Stationarity
Lassi Meronen
Martin Trapp
Arno Solin
BDL
84
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26 Oct 2021
Variational Gaussian Processes: A Functional Analysis View
Variational Gaussian Processes: A Functional Analysis View
Veit Wild
George Wynne
GP
78
5
0
25 Oct 2021
Nonnegative spatial factorization
Nonnegative spatial factorization
F. W. Townes
Barbara E. Engelhardt
35
11
0
12 Oct 2021
Efficient Fourier representations of families of Gaussian processes
Efficient Fourier representations of families of Gaussian processes
P. Greengard
77
3
0
28 Sep 2021
Contraction rates for sparse variational approximations in Gaussian
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Contraction rates for sparse variational approximations in Gaussian process regression
D. Nieman
Botond Szabó
Harry Van Zanten
111
17
0
22 Sep 2021
Large-Scale Learning with Fourier Features and Tensor Decompositions
Large-Scale Learning with Fourier Features and Tensor Decompositions
Frederiek Wesel
Kim Batselier
39
11
0
03 Sep 2021
Adaptive Inducing Points Selection For Gaussian Processes
Adaptive Inducing Points Selection For Gaussian Processes
Théo Galy-Fajou
Manfred Opper
84
16
0
21 Jul 2021
Spectrum Gaussian Processes Based On Tunable Basis Functions
Spectrum Gaussian Processes Based On Tunable Basis Functions
Wenqi Fang
Guanlin Wu
Jingjing Li
Ziyi Wang
Jiang Cao
Yang Ping
13
0
0
14 Jul 2021
Combining Pseudo-Point and State Space Approximations for Sum-Separable
  Gaussian Processes
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian Processes
Will Tebbutt
Arno Solin
Richard Turner
56
8
0
18 Jun 2021
Marginalising over Stationary Kernels with Bayesian Quadrature
Marginalising over Stationary Kernels with Bayesian Quadrature
Saad Hamid
Sebastian Schulze
Michael A. Osborne
Stephen J. Roberts
GP
43
4
0
14 Jun 2021
Scalable Variational Gaussian Processes via Harmonic Kernel
  Decomposition
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun
Jiaxin Shi
A. Wilson
Roger C. Grosse
BDL
31
7
0
10 Jun 2021
Connections and Equivalences between the Nyström Method and Sparse
  Variational Gaussian Processes
Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes
Veit Wild
Motonobu Kanagawa
Dino Sejdinovic
81
16
0
02 Jun 2021
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
Vincent Dutordoir
J. Hensman
Mark van der Wilk
Carl Henrik Ek
Zoubin Ghahramani
N. Durrande
BDLUQCV
103
31
0
10 May 2021
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
M. Lemercier
C. Salvi
Thomas Cass
Edwin V. Bonilla
Theodoros Damoulas
Terry Lyons
61
25
0
10 May 2021
MetaKernel: Learning Variational Random Features with Limited Labels
MetaKernel: Learning Variational Random Features with Limited Labels
Yingjun Du
Haoliang Sun
Xiantong Zhen
Jun Xu
Yilong Yin
Ling Shao
Cees G. M. Snoek
VLMBDL
32
5
0
08 May 2021
Dense Incremental Metric-Semantic Mapping for Multi-Agent Systems via
  Sparse Gaussian Process Regression
Dense Incremental Metric-Semantic Mapping for Multi-Agent Systems via Sparse Gaussian Process Regression
Ehsan Zobeidi
Alec Koppel
Nikolay Atanasov
61
13
0
30 Mar 2021
Sparse Algorithms for Markovian Gaussian Processes
Sparse Algorithms for Markovian Gaussian Processes
William J. Wilkinson
Arno Solin
Vincent Adam
50
12
0
19 Mar 2021
Recent Advances in Data-Driven Wireless Communication Using Gaussian
  Processes: A Comprehensive Survey
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey
Kai Chen
Qinglei Kong
Yijue Dai
Yue Xu
Feng Yin
Lexi Xu
Shuguang Cui
102
30
0
18 Mar 2021
Temporal Gaussian Process Regression in Logarithmic Time
Temporal Gaussian Process Regression in Logarithmic Time
Adrien Corenflos
Zheng Zhao
Simo Särkkä
46
3
0
19 Feb 2021
Reducing the Amortization Gap in Variational Autoencoders: A Bayesian
  Random Function Approach
Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach
Minyoung Kim
Vladimir Pavlovic
BDL
91
6
0
05 Feb 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference
A Tutorial on Sparse Gaussian Processes and Variational Inference
Felix Leibfried
Vincent Dutordoir
S. T. John
N. Durrande
GP
127
51
0
27 Dec 2020
Pathwise Conditioning of Gaussian Processes
Pathwise Conditioning of Gaussian Processes
James T. Wilson
Viacheslav Borovitskiy
Alexander Terenin
P. Mostowsky
M. Deisenroth
102
61
0
08 Nov 2020
Inter-domain Deep Gaussian Processes
Inter-domain Deep Gaussian Processes
Tim G. J. Rudner
Dino Sejdinovic
Yarin Gal
79
11
0
01 Nov 2020
Matérn Gaussian Processes on Graphs
Matérn Gaussian Processes on Graphs
Viacheslav Borovitskiy
I. Azangulov
Alexander Terenin
P. Mostowsky
M. Deisenroth
N. Durrande
51
82
0
29 Oct 2020
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
S. Popescu
D. Sharp
James H. Cole
Ben Glocker
72
5
0
28 Oct 2020
Scalable Bayesian Optimization with Sparse Gaussian Process Models
Scalable Bayesian Optimization with Sparse Gaussian Process Models
Ang Yang
50
0
0
26 Oct 2020
Semi-parametric $γ$-ray modeling with Gaussian processes and
  variational inference
Semi-parametric γγγ-ray modeling with Gaussian processes and variational inference
S. Mishra-Sharma
Kyle Cranmer
MedIm
102
7
0
20 Oct 2020
Stationary Activations for Uncertainty Calibration in Deep Learning
Stationary Activations for Uncertainty Calibration in Deep Learning
Lassi Meronen
Christabella Irwanto
Arno Solin
UQCVBDL
54
19
0
19 Oct 2020
Probabilistic selection of inducing points in sparse Gaussian processes
Probabilistic selection of inducing points in sparse Gaussian processes
Anders Kirk Uhrenholt
V. Charvet
B. S. Jensen
21
13
0
19 Oct 2020
Convergence of Sparse Variational Inference in Gaussian Processes
  Regression
Convergence of Sparse Variational Inference in Gaussian Processes Regression
David R. Burt
C. Rasmussen
Mark van der Wilk
82
74
0
01 Aug 2020
Orthogonally Decoupled Variational Fourier Features
Orthogonally Decoupled Variational Fourier Features
Dario Azzimonti
Manuel Schürch
A. Benavoli
Marco Zaffalon
15
0
0
13 Jul 2020
Sparse Gaussian Processes with Spherical Harmonic Features
Sparse Gaussian Processes with Spherical Harmonic Features
Vincent Dutordoir
N. Durrande
J. Hensman
71
56
0
30 Jun 2020
Variational Orthogonal Features
Variational Orthogonal Features
David R. Burt
C. Rasmussen
Mark van der Wilk
BDLDRL
63
12
0
23 Jun 2020
Fast Matrix Square Roots with Applications to Gaussian Processes and
  Bayesian Optimization
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
Geoff Pleiss
M. Jankowiak
David Eriksson
Anil Damle
Jacob R. Gardner
80
43
0
19 Jun 2020
Latent variable modeling with random features
Latent variable modeling with random features
Gregory W. Gundersen
M. Zhang
Barbara E. Engelhardt
BDLDRL
41
11
0
19 Jun 2020
Kernel methods through the roof: handling billions of points efficiently
Kernel methods through the roof: handling billions of points efficiently
Giacomo Meanti
Luigi Carratino
Lorenzo Rosasco
Alessandro Rudi
90
116
0
18 Jun 2020
Matérn Gaussian processes on Riemannian manifolds
Matérn Gaussian processes on Riemannian manifolds
Viacheslav Borovitskiy
Alexander Terenin
P. Mostowsky
M. Deisenroth
126
123
0
17 Jun 2020
A Survey of Constrained Gaussian Process Regression: Approaches and
  Implementation Challenges
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges
L. Swiler
Mamikon A. Gulian
A. Frankel
Cosmin Safta
J. Jakeman
GPAI4CE
91
106
0
16 Jun 2020
The Statistical Cost of Robust Kernel Hyperparameter Tuning
The Statistical Cost of Robust Kernel Hyperparameter Tuning
R. A. Meyer
Christopher Musco
60
2
0
14 Jun 2020
Learning to Learn Kernels with Variational Random Features
Learning to Learn Kernels with Variational Random Features
Xiantong Zhen
Hao Sun
Yingjun Du
Jun Xu
Yilong Yin
Ling Shao
Cees G. M. Snoek
DRL
72
34
0
11 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models
Scalable Thompson Sampling using Sparse Gaussian Process Models
Sattar Vakili
Henry B. Moss
A. Artemev
Vincent Dutordoir
Victor Picheny
71
35
0
09 Jun 2020
Practical Hilbert space approximate Bayesian Gaussian processes for
  probabilistic programming
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming
Gabriel Riutort-Mayol
Paul-Christian Bürkner
Michael R. Andersen
Arno Solin
Aki Vehtari
84
72
0
23 Apr 2020
How Good are Low-Rank Approximations in Gaussian Process Regression?
How Good are Low-Rank Approximations in Gaussian Process Regression?
C. Daskalakis
P. Dellaportas
A. Panos
60
3
0
03 Apr 2020
SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for
  Gaussian Process Regression with Derivatives
SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives
Emmanouil Angelis
Philippe Wenk
Bernhard Schölkopf
Stefan Bauer
Andreas Krause
BDL
62
3
0
05 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes
A Framework for Interdomain and Multioutput Gaussian Processes
Mark van der Wilk
Vincent Dutordoir
S. T. John
A. Artemev
Vincent Adam
J. Hensman
100
95
0
02 Mar 2020
Efficiently Sampling Functions from Gaussian Process Posteriors
Efficiently Sampling Functions from Gaussian Process Posteriors
James T. Wilson
Viacheslav Borovitskiy
Alexander Terenin
P. Mostowsky
M. Deisenroth
79
165
0
21 Feb 2020
Sparse Recovery With Non-Linear Fourier Features
Sparse Recovery With Non-Linear Fourier Features
Ayça Özçelikkale
50
5
0
12 Feb 2020
Doubly Sparse Variational Gaussian Processes
Doubly Sparse Variational Gaussian Processes
Vincent Adam
Stefanos Eleftheriadis
N. Durrande
A. Artemev
J. Hensman
82
26
0
15 Jan 2020
The Wasserstein-Fourier Distance for Stationary Time Series
The Wasserstein-Fourier Distance for Stationary Time Series
Elsa Cazelles
Arnaud Robert
Felipe A. Tobar
AI4TS
48
35
0
11 Dec 2019
Gaussian Process Priors for View-Aware Inference
Gaussian Process Priors for View-Aware Inference
Wenshuai Zhao
Ari Heljakka
Arno Solin
BDL
35
1
0
06 Dec 2019
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