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Bayesian Deep Ensembles via the Neural Tangent Kernel

Bayesian Deep Ensembles via the Neural Tangent Kernel

11 July 2020
Bobby He
Balaji Lakshminarayanan
Yee Whye Teh
    BDL
    UQCV
ArXivPDFHTML

Papers citing "Bayesian Deep Ensembles via the Neural Tangent Kernel"

34 / 34 papers shown
Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
L. J. L. Lopez
Shaza Elsharief
Dhiyaa Al Jorf
Firas Darwish
Congbo Ma
Farah E. Shamout
110
0
0
04 May 2025
Position: Enough of Scaling LLMs! Lets Focus on Downscaling
Position: Enough of Scaling LLMs! Lets Focus on Downscaling
Ayan Sengupta
Yash Goel
Tanmoy Chakraborty
34
0
0
02 May 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
Moritz A. Zanger
Pascal R. van der Vaart
Wendelin Bohmer
M. Spaan
UQCV
BDL
149
0
0
14 Mar 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
Kaizheng Wang
Keivan K1 Shariatmadar
Shireen Kudukkil Manchingal
Fabio Cuzzolin
David Moens
Hans Hallez
UQCV
BDL
92
12
0
28 Jan 2025
Continual learning with the neural tangent ensemble
Continual learning with the neural tangent ensemble
Ari S. Benjamin
Christian Pehle
Kyle Daruwalla
UQCV
70
0
0
30 Aug 2024
Neural Lineage
Neural Lineage
Runpeng Yu
Xinchao Wang
34
4
0
17 Jun 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang
Fabio Cuzzolin
Keivan K1 Shariatmadar
David Moens
Hans Hallez
UQCV
BDL
85
6
0
23 May 2024
Active Few-Shot Fine-Tuning
Active Few-Shot Fine-Tuning
Jonas Hübotter
Bhavya Sukhija
Lenart Treven
Yarden As
Andreas Krause
45
1
0
13 Feb 2024
Training-Free Neural Active Learning with Initialization-Robustness
  Guarantees
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
Apivich Hemachandra
Zhongxiang Dai
Jasraj Singh
See-Kiong Ng
K. H. Low
AAML
36
6
0
07 Jun 2023
Toward Robust Uncertainty Estimation with Random Activation Functions
Toward Robust Uncertainty Estimation with Random Activation Functions
Y. Stoyanova
Soroush Ghandi
M. Tavakol
UQCV
26
2
0
28 Feb 2023
Width and Depth Limits Commute in Residual Networks
Width and Depth Limits Commute in Residual Networks
Soufiane Hayou
Greg Yang
42
14
0
01 Feb 2023
Learning Skills from Demonstrations: A Trend from Motion Primitives to
  Experience Abstraction
Learning Skills from Demonstrations: A Trend from Motion Primitives to Experience Abstraction
Mehrdad Tavassoli
S. Katyara
Maria Pozzi
Nikhil Deshpande
D. Caldwell
D. Prattichizzo
25
11
0
14 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent
  Kernel
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
Sungyub Kim
Si-hun Park
Kyungsu Kim
Eunho Yang
BDL
29
4
0
30 Sep 2022
Single Model Uncertainty Estimation via Stochastic Data Centering
Single Model Uncertainty Estimation via Stochastic Data Centering
Jayaraman J. Thiagarajan
Rushil Anirudh
V. Narayanaswamy
P. Bremer
UQCV
OOD
25
26
0
14 Jul 2022
Fast Finite Width Neural Tangent Kernel
Fast Finite Width Neural Tangent Kernel
Roman Novak
Jascha Narain Sohl-Dickstein
S. Schoenholz
AAML
22
53
0
17 Jun 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and
  Bootstrapping
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping
Vikranth Dwaracherla
Zheng Wen
Ian Osband
Xiuyuan Lu
S. Asghari
Benjamin Van Roy
UQCV
24
17
0
08 Jun 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit
  Composite Kernel
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel
Ziyang Jiang
Tongshu Zheng
Yiling Liu
David Carlson
30
4
0
15 May 2022
Bayesian Deep Learning with Multilevel Trace-class Neural Networks
Bayesian Deep Learning with Multilevel Trace-class Neural Networks
Neil K. Chada
Ajay Jasra
K. Law
Sumeetpal S. Singh
BDL
UQCV
83
3
0
24 Mar 2022
Contrasting random and learned features in deep Bayesian linear
  regression
Contrasting random and learned features in deep Bayesian linear regression
Jacob A. Zavatone-Veth
William L. Tong
C. Pehlevan
BDL
MLT
28
26
0
01 Mar 2022
Theoretical Error Analysis of Entropy Approximation for Gaussian Mixture
Theoretical Error Analysis of Entropy Approximation for Gaussian Mixture
Takashi Furuya
Hiroyuki Kusumoto
K. Taniguchi
Naoya Kanno
Kazuma Suetake
19
1
0
26 Feb 2022
Deep Ensembles Work, But Are They Necessary?
Deep Ensembles Work, But Are They Necessary?
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
R. Zemel
John P. Cunningham
OOD
UQCV
44
59
0
14 Feb 2022
The Neural Testbed: Evaluating Joint Predictions
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
29
20
0
09 Oct 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks
  with Sparse Gaussian Processes
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes
Jongseo Lee
Jianxiang Feng
Matthias Humt
M. Müller
Rudolph Triebel
UQCV
48
21
0
20 Sep 2021
Reliable Neural Networks for Regression Uncertainty Estimation
Reliable Neural Networks for Regression Uncertainty Estimation
Tony Tohme
Kevin Vanslette
K. Youcef-Toumi
UQCV
BDL
18
15
0
16 Sep 2021
A framework for benchmarking uncertainty in deep regression
A framework for benchmarking uncertainty in deep regression
F. Schmähling
Jörg Martin
Clemens Elster
UQCV
38
8
0
10 Sep 2021
Repulsive Deep Ensembles are Bayesian
Repulsive Deep Ensembles are Bayesian
Francesco DÁngelo
Vincent Fortuin
UQCV
BDL
53
94
0
22 Jun 2021
A self consistent theory of Gaussian Processes captures feature learning
  effects in finite CNNs
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
Gadi Naveh
Z. Ringel
SSL
MLT
36
31
0
08 Jun 2021
Priors in Bayesian Deep Learning: A Review
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
UQCV
BDL
31
124
0
14 May 2021
Deep Deterministic Uncertainty: A Simple Baseline
Deep Deterministic Uncertainty: A Simple Baseline
Jishnu Mukhoti
Andreas Kirsch
Joost R. van Amersfoort
Philip Torr
Y. Gal
UD
UQCV
PER
BDL
24
145
0
23 Feb 2021
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
42
24
0
27 Oct 2020
Stable ResNet
Stable ResNet
Soufiane Hayou
Eugenio Clerico
Bo He
George Deligiannidis
Arnaud Doucet
Judith Rousseau
ODL
SSeg
46
51
0
24 Oct 2020
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Sheheryar Zaidi
Arber Zela
T. Elsken
Chris Holmes
Frank Hutter
Yee Whye Teh
OOD
UQCV
18
71
0
15 Jun 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
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
9,138
0
06 Jun 2015
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