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2302.10975
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Improved uncertainty quantification for neural networks with Bayesian last layer
21 February 2023
F. Fiedler
S. Lucia
UQCV
BDL
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Papers citing
"Improved uncertainty quantification for neural networks with Bayesian last layer"
11 / 11 papers shown
Title
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Philipp Reiser
Javier Enrique Aguilar
A. Guthke
Paul-Christian Bürkner
135
3
0
08 Dec 2023
Learning in High Dimension Always Amounts to Extrapolation
Randall Balestriero
J. Pesenti
Yann LeCun
117
104
0
18 Oct 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
346
1,932
0
12 Nov 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Laurent Valentin Jospin
Wray Buntine
F. Boussaïd
Hamid Laga
Bennamoun
OOD
BDL
UQCV
86
631
0
14 Jul 2020
Deep Latent-Variable Kernel Learning
Haitao Liu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
BDL
51
8
0
18 May 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
J. Swiatkowski
Kevin Roth
Bastiaan S. Veeling
Linh-Tam Tran
Joshua V. Dillon
Jasper Snoek
Stephan Mandt
Tim Salimans
Rodolphe Jenatton
Sebastian Nowozin
BDL
54
46
0
07 Feb 2020
Benchmarking the Neural Linear Model for Regression
Sebastian W. Ober
C. Rasmussen
BDL
72
43
0
18 Dec 2019
When Gaussian Process Meets Big Data: A Review of Scalable GPs
Haitao Liu
Yew-Soon Ong
Xiaobo Shen
Jianfei Cai
GP
101
693
0
03 Jul 2018
Deep Kernel Learning
A. Wilson
Zhiting Hu
Ruslan Salakhutdinov
Eric Xing
BDL
256
889
0
06 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
856
9,353
0
06 Jun 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
467
43,347
0
11 Feb 2015
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