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2007.05864
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Bayesian Deep Ensembles via the Neural Tangent Kernel
11 July 2020
Bobby He
Balaji Lakshminarayanan
Yee Whye Teh
BDL
UQCV
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Papers citing
"Bayesian Deep Ensembles via the Neural Tangent Kernel"
35 / 85 papers shown
Title
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel
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Tongshu Zheng
Yiling Liu
David Carlson
73
4
0
15 May 2022
Deep Ensemble as a Gaussian Process Approximate Posterior
Zhijie Deng
Feng Zhou
Jianfei Chen
Guoqiang Wu
Jun Zhu
UQCV
46
5
0
30 Apr 2022
Contrasting random and learned features in deep Bayesian linear regression
Jacob A. Zavatone-Veth
William L. Tong
Cengiz Pehlevan
BDL
MLT
137
28
0
01 Mar 2022
Theoretical Error Analysis of Entropy Approximation for Gaussian Mixture
Takashi Furuya
Hiroyuki Kusumoto
K. Taniguchi
Naoya Kanno
Kazuma Suetake
88
1
0
26 Feb 2022
Embedded Ensembles: Infinite Width Limit and Operating Regimes
Maksim Velikanov
Roma Kail
Ivan Anokhin
Roman Vashurin
Maxim Panov
Alexey Zaytsev
Dmitry Yarotsky
49
1
0
24 Feb 2022
Wide Mean-Field Bayesian Neural Networks Ignore the Data
Beau Coker
W. Bruinsma
David R. Burt
Weiwei Pan
Finale Doshi-Velez
UQCV
BDL
89
24
0
23 Feb 2022
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography
Francisca Vasconcelos
Bobby He
Nalini Singh
Yee Whye Teh
BDL
OOD
UQCV
76
13
0
22 Feb 2022
Deep Ensembles Work, But Are They Necessary?
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
R. Zemel
John P. Cunningham
OOD
UQCV
147
65
0
14 Feb 2022
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks
Florian Juengermann
Maxime Laasri
Marius Merkle
BDL
36
0
0
13 Jan 2022
Empirical analysis of representation learning and exploration in neural kernel bandits
Michal Lisicki
Arash Afkanpour
Graham W. Taylor
55
0
0
05 Nov 2021
Quantifying Epistemic Uncertainty in Deep Learning
Ziyi Huang
Henry Lam
Haofeng Zhang
UQCV
BDL
UD
PER
134
14
0
23 Oct 2021
Conditional Variational Autoencoder for Learned Image Reconstruction
Chen Zhang
Riccardo Barbano
Bangti Jin
DRL
51
20
0
22 Oct 2021
The Neural Testbed: Evaluating Joint Predictions
Ian Osband
Zheng Wen
S. Asghari
Vikranth Dwaracherla
Botao Hao
M. Ibrahimi
Dieterich Lawson
Xiuyuan Lu
Brendan O'Donoghue
Benjamin Van Roy
UQCV
94
22
0
09 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation
Dennis Ulmer
Christian Hardmeier
J. Frellsen
BDL
UQCV
UD
EDL
PER
150
55
0
06 Oct 2021
Marginally calibrated response distributions for end-to-end learning in autonomous driving
Clara Hoffmann
Nadja Klein
89
2
0
03 Oct 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes
Jongseo Lee
Jianxiang Feng
Matthias Humt
M. Müller
Rudolph Triebel
UQCV
92
21
0
20 Sep 2021
Reliable Neural Networks for Regression Uncertainty Estimation
Tony Tohme
Kevin Vanslette
K. Youcef-Toumi
UQCV
BDL
85
15
0
16 Sep 2021
A framework for benchmarking uncertainty in deep regression
F. Schmähling
Jörg Martin
Clemens Elster
UQCV
64
8
0
10 Sep 2021
Epistemic Neural Networks
Ian Osband
Zheng Wen
M. Asghari
Vikranth Dwaracherla
M. Ibrahimi
Xiyuan Lu
Benjamin Van Roy
UQCV
BDL
136
109
0
19 Jul 2021
Repulsive Deep Ensembles are Bayesian
Francesco DÁngelo
Vincent Fortuin
UQCV
BDL
129
101
0
22 Jun 2021
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
Gadi Naveh
Zohar Ringel
SSL
MLT
91
33
0
08 Jun 2021
Greedy Bayesian Posterior Approximation with Deep Ensembles
A. Tiulpin
Matthew B. Blaschko
UQCV
FedML
91
4
0
29 May 2021
Deep Ensembles from a Bayesian Perspective
L. Hoffmann
Clemens Elster
UD
BDL
UQCV
74
38
0
27 May 2021
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
UQCV
BDL
137
134
0
14 May 2021
Uncertainty-aware Remaining Useful Life predictor
Luca Biggio
Alexander Wieland
M. A. Chao
I. Kastanis
Olga Fink
AI4CE
32
7
0
08 Apr 2021
MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks
Alexandre Ramé
Rémy Sun
Matthieu Cord
UQCV
108
60
0
10 Mar 2021
Deep Deterministic Uncertainty: A Simple Baseline
Jishnu Mukhoti
Andreas Kirsch
Joost R. van Amersfoort
Philip Torr
Y. Gal
UD
UQCV
PER
BDL
129
156
0
23 Feb 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Li Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDL
UQCV
373
1,951
0
12 Nov 2020
A Bayesian Perspective on Training Speed and Model Selection
Clare Lyle
Lisa Schut
Binxin Ru
Y. Gal
Mark van der Wilk
102
24
0
27 Oct 2020
Stable ResNet
Soufiane Hayou
Eugenio Clerico
Bo He
George Deligiannidis
Arnaud Doucet
Judith Rousseau
ODL
SSeg
103
53
0
24 Oct 2020
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning
Zhijie Deng
Jun Zhu
BDL
48
9
0
05 Oct 2020
On Power Laws in Deep Ensembles
E. Lobacheva
Nadezhda Chirkova
M. Kodryan
Dmitry Vetrov
UQCV
75
40
0
16 Jul 2020
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Sheheryar Zaidi
Arber Zela
T. Elsken
Chris Holmes
Frank Hutter
Yee Whye Teh
OOD
UQCV
130
75
0
15 Jun 2020
PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction
Eli Simhayev
Gilad Katz
Lior Rokach
OOD
51
12
0
09 Jun 2020
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
Ryo Karakida
S. Akaho
S. Amari
FedML
201
146
0
04 Jun 2018
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