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Doubly Stochastic Variational Inference for Deep Gaussian Processes
v1v2 (latest)

Doubly Stochastic Variational Inference for Deep Gaussian Processes

24 May 2017
Hugh Salimbeni
M. Deisenroth
    BDLGP
ArXiv (abs)PDFHTML

Papers citing "Doubly Stochastic Variational Inference for Deep Gaussian Processes"

38 / 238 papers shown
Interpretable deep Gaussian processes with moments
Interpretable deep Gaussian processes with momentsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Chi-Ken Lu
Scott Cheng-Hsin Yang
Xiaoran Hao
Patrick Shafto
230
19
0
27 May 2019
Learning spectrograms with convolutional spectral kernels
Learning spectrograms with convolutional spectral kernelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Zheyan Shen
Markus Heinonen
Samuel Kaski
170
9
0
23 May 2019
Deep Gaussian Processes with Importance-Weighted Variational Inference
Deep Gaussian Processes with Importance-Weighted Variational InferenceInternational Conference on Machine Learning (ICML), 2019
Hugh Salimbeni
Vincent Dutordoir
J. Hensman
M. Deisenroth
BDL
237
44
0
14 May 2019
Bayesian Optimization using Deep Gaussian Processes
Bayesian Optimization using Deep Gaussian ProcessesOptimization and Engineering (Optim. Eng.), 2019
Ali Hebbal
Loïc Brevault
M. Balesdent
El-Ghazali Talbi
N. Melab
GP
214
76
0
07 May 2019
Robust Deep Gaussian Processes
Robust Deep Gaussian Processes
Jeremias Knoblauch
GP
223
17
0
04 Apr 2019
Generalized Variational Inference: Three arguments for deriving new
  Posteriors
Generalized Variational Inference: Three arguments for deriving new Posteriors
Jeremias Knoblauch
Jack Jewson
Theodoros Damoulas
DRLBDL
492
114
0
03 Apr 2019
Exact Gaussian Processes on a Million Data Points
Exact Gaussian Processes on a Million Data PointsNeural Information Processing Systems (NeurIPS), 2019
Ke Alexander Wang
Geoff Pleiss
Jacob R. Gardner
Stephen Tyree
Kilian Q. Weinberger
A. Wilson
GP
321
248
0
19 Mar 2019
Deep Gaussian Processes for Multi-fidelity Modeling
Deep Gaussian Processes for Multi-fidelity Modeling
Kurt Cutajar
Mark Pullin
Andreas C. Damianou
Neil D. Lawrence
Javier I. González
AI4CE
157
119
0
18 Mar 2019
Functional Variational Bayesian Neural Networks
Functional Variational Bayesian Neural Networks
Shengyang Sun
Guodong Zhang
Jiaxin Shi
Roger C. Grosse
BDL
260
257
0
14 Mar 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes
Bayesian Image Classification with Deep Convolutional Gaussian Processes
Vincent Dutordoir
Mark van der Wilk
A. Artemev
J. Hensman
UQCVBDL
290
36
0
15 Feb 2019
Scalable GAM using sparse variational Gaussian processes
Scalable GAM using sparse variational Gaussian processes
Vincent Adam
N. Durrande
S. T. John
96
2
0
28 Dec 2018
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete
  Demonstrations of Algorithmic Effectiveness in the Machine Learning and
  Artificial Intelligence Literature
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature
Franz J. Király
Bilal A. Mateen
R. Sonabend
198
10
0
18 Dec 2018
Non-Factorised Variational Inference in Dynamical Systems
Non-Factorised Variational Inference in Dynamical Systems
Alessandro Davide Ialongo
Mark van der Wilk
J. Hensman
C. Rasmussen
168
6
0
14 Dec 2018
Bayesian Layers: A Module for Neural Network Uncertainty
Bayesian Layers: A Module for Neural Network Uncertainty
Dustin Tran
Michael W. Dusenberry
Mark van der Wilk
Danijar Hafner
UQCVBDL
330
136
0
10 Dec 2018
Data Association with Gaussian Processes
Data Association with Gaussian Processes
Markus Kaiser
Clemens Otte
Thomas Runkler
Carl Henrik Ek
169
0
0
16 Oct 2018
Harmonizable mixture kernels with variational Fourier features
Harmonizable mixture kernels with variational Fourier features
Zheyan Shen
Markus Heinonen
Samuel Kaski
241
17
0
10 Oct 2018
Deep learning with differential Gaussian process flows
Deep learning with differential Gaussian process flows
Pashupati Hegde
Markus Heinonen
Harri Lähdesmäki
Samuel Kaski
BDL
203
43
0
09 Oct 2018
Deep convolutional Gaussian processes
Deep convolutional Gaussian processes
Kenneth Blomqvist
Samuel Kaski
Markus Heinonen
BDL
161
63
0
06 Oct 2018
InfoSSM: Interpretable Unsupervised Learning of Nonparametric
  State-Space Model for Multi-modal Dynamics
InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics
Young-Jin Park
Han-Lim Choi
102
0
0
19 Sep 2018
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Yin Cheng Ng
Nicolo Colombo
Ricardo M. A. Silva
BDL
333
93
0
12 Sep 2018
Efficient Global Optimization using Deep Gaussian Processes
Efficient Global Optimization using Deep Gaussian Processes
Ali Hebbal
Loïc Brevault
M. Balesdent
El-Ghazali Talbi
N. Melab
115
20
0
11 Sep 2018
Structured Bayesian Gaussian process latent variable model: applications
  to data-driven dimensionality reduction and high-dimensional inversion
Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion
Steven Atkinson
N. Zabaras
126
38
0
11 Jul 2018
Conditional Neural Processes
Conditional Neural ProcessesInternational Conference on Machine Learning (ICML), 2018
M. Garnelo
Dan Rosenbaum
Chris J. Maddison
Tiago Ramalho
D. Saxton
Murray Shanahan
Yee Whye Teh
Danilo Jimenez Rezende
S. M. Ali Eslami
UQCVBDL
362
778
0
04 Jul 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs
When Gaussian Process Meets Big Data: A Review of Scalable GPsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018
Haitao Liu
Yew-Soon Ong
Xiaobo Shen
Jianfei Cai
GP
410
806
0
03 Jul 2018
Inference in Deep Gaussian Processes using Stochastic Gradient
  Hamiltonian Monte Carlo
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
Marton Havasi
José Miguel Hernández-Lobato
J. J. Murillo-Fuentes
BDL
223
105
0
14 Jun 2018
Building Bayesian Neural Networks with Blocks: On Structure,
  Interpretability and Uncertainty
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty
Hao Zhou
Yunyang Xiong
Vikas Singh
UQCVBDL
152
4
0
10 Jun 2018
Deep Gaussian Processes with Convolutional Kernels
Deep Gaussian Processes with Convolutional Kernels
Vinayak Kumar
Vaibhav Singh
P. K. Srijith
Andreas C. Damianou
BDLGP
169
32
0
05 Jun 2018
Deep Mixed Effect Model using Gaussian Processes: A Personalized and
  Reliable Prediction for Healthcare
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare
Ingyo Chung
Saehoon Kim
Juho Lee
Kwang Joon Kim
Sung Ju Hwang
Eunho Yang
BDLFedML
224
19
0
05 Jun 2018
Structured Bayesian Gaussian process latent variable model
Structured Bayesian Gaussian process latent variable model
Steven Atkinson
N. Zabaras
126
5
0
22 May 2018
Variational zero-inflated Gaussian processes with sparse kernels
Variational zero-inflated Gaussian processes with sparse kernelsConference on Uncertainty in Artificial Intelligence (UAI), 2018
Pashupati Hegde
Markus Heinonen
Samuel Kaski
85
7
0
13 Mar 2018
Probabilistic Recurrent State-Space Models
Probabilistic Recurrent State-Space Models
Andreas Doerr
Christian Daniel
Martin Schiegg
D. Nguyen-Tuong
S. Schaal
Marc Toussaint
Sebastian Trimpe
298
135
0
31 Jan 2018
Deep Gaussian Processes with Decoupled Inducing Inputs
Deep Gaussian Processes with Decoupled Inducing Inputs
Marton Havasi
José Miguel Hernández-Lobato
J. J. Murillo-Fuentes
GPUQCVBDL
55
7
0
09 Jan 2018
How Deep Are Deep Gaussian Processes?
How Deep Are Deep Gaussian Processes?
Matthew M. Dunlop
Mark Girolami
Andrew M. Stuart
A. Teckentrup
GP
190
138
0
30 Nov 2017
Gaussian Process Neurons Learn Stochastic Activation Functions
Gaussian Process Neurons Learn Stochastic Activation Functions
Sebastian Urban
Marcus Basalla
Patrick van der Smagt
BDL
111
5
0
29 Nov 2017
Structured Variational Inference for Coupled Gaussian Processes
Structured Variational Inference for Coupled Gaussian Processes
Vincent Adam
116
2
0
03 Nov 2017
Deep Recurrent Gaussian Process with Variational Sparse Spectrum
  Approximation
Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation
Roman Föll
B. Haasdonk
Markus Hanselmann
Holger Ulmer
BDL
143
6
0
02 Nov 2017
Bayesian Alignments of Warped Multi-Output Gaussian Processes
Bayesian Alignments of Warped Multi-Output Gaussian Processes
Markus Kaiser
Clemens Otte
Thomas Runkler
Carl Henrik Ek
178
19
0
08 Oct 2017
Generic Inference in Latent Gaussian Process Models
Generic Inference in Latent Gaussian Process Models
Edwin V. Bonilla
K. Krauth
Amir Dezfouli
BDL
269
29
0
02 Sep 2016
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