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Bayesian Image Classification with Deep Convolutional Gaussian Processes

Bayesian Image Classification with Deep Convolutional Gaussian Processes

15 February 2019
Vincent Dutordoir
Mark van der Wilk
A. Artemev
J. Hensman
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Bayesian Image Classification with Deep Convolutional Gaussian Processes"

13 / 13 papers shown
Title
Robust and Conjugate Gaussian Process Regression
Robust and Conjugate Gaussian Process Regression
Matias Altamirano
F. Briol
Jeremias Knoblauch
18
10
0
01 Nov 2023
Skew Class-balanced Re-weighting for Unbiased Scene Graph Generation
Skew Class-balanced Re-weighting for Unbiased Scene Graph Generation
Haeyong Kang
Chang-Dong Yoo
30
6
0
01 Jan 2023
Distributional Gaussian Processes Layers for Out-of-Distribution
  Detection
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
OOD
21
0
0
27 Jun 2022
Geometry-Aware Hierarchical Bayesian Learning on Manifolds
Geometry-Aware Hierarchical Bayesian Learning on Manifolds
Yonghui Fan
Yalin Wang
13
2
0
30 Oct 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian
  Process Perspective
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
Geoff Pleiss
John P. Cunningham
26
24
0
11 Jun 2021
Priors in Bayesian Deep Learning: A Review
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
UQCV
BDL
29
124
0
14 May 2021
GPflux: A Library for Deep Gaussian Processes
GPflux: A Library for Deep Gaussian Processes
Vincent Dutordoir
Hugh Salimbeni
Eric Hambro
John Mcleod
Felix Leibfried
A. Artemev
Mark van der Wilk
J. Hensman
M. Deisenroth
S. T. John
GP
28
23
0
12 Apr 2021
The Promises and Pitfalls of Deep Kernel Learning
The Promises and Pitfalls of Deep Kernel Learning
Sebastian W. Ober
C. Rasmussen
Mark van der Wilk
UQCV
BDL
21
107
0
24 Feb 2021
Pathwise Conditioning of Gaussian Processes
Pathwise Conditioning of Gaussian Processes
James T. Wilson
Viacheslav Borovitskiy
Alexander Terenin
P. Mostowsky
M. Deisenroth
13
57
0
08 Nov 2020
A Bayesian Perspective on Training Speed and Model Selection
A Bayesian Perspective on Training Speed and Model Selection
Clare Lyle
Lisa Schut
Binxin Ru
Y. Gal
Mark van der Wilk
34
23
0
27 Oct 2020
Global inducing point variational posteriors for Bayesian neural
  networks and deep Gaussian processes
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W. Ober
Laurence Aitchison
BDL
15
60
0
17 May 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
37
94
0
02 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
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