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Tractable Function-Space Variational Inference in Bayesian Neural
  Networks

Tractable Function-Space Variational Inference in Bayesian Neural Networks

28 December 2023
Tim G. J. Rudner
Zonghao Chen
Yee Whye Teh
Y. Gal
ArXivPDFHTML

Papers citing "Tractable Function-Space Variational Inference in Bayesian Neural Networks"

11 / 11 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
98
0
0
04 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
137
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
Variational Inference Failures Under Model Symmetries: Permutation
  Invariant Posteriors for Bayesian Neural Networks
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks
Yoav Gelberg
Tycho F. A. van der Ouderaa
Mark van der Wilk
Y. Gal
AAML
35
4
0
10 Aug 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
77
6
0
23 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural
  Networks
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
Yunzhen Feng
Tim G. J. Rudner
Nikolaos Tsilivis
Julia Kempe
AAML
BDL
43
1
0
27 Apr 2024
CARD: Classification and Regression Diffusion Models
CARD: Classification and Regression Diffusion Models
Xizewen Han
Huangjie Zheng
Mingyuan Zhou
DiffM
38
108
0
15 Jun 2022
Split personalities in Bayesian Neural Networks: the case for full
  marginalisation
Split personalities in Bayesian Neural Networks: the case for full marginalisation
David Yallup
Will Handley
Michael P. Hobson
A. Lasenby
Pablo Lemos
20
1
0
23 May 2022
Unsolved Problems in ML Safety
Unsolved Problems in ML Safety
Dan Hendrycks
Nicholas Carlini
John Schulman
Jacob Steinhardt
175
273
0
28 Sep 2021
Scalable Uncertainty for Computer Vision with Functional Variational
  Inference
Scalable Uncertainty for Computer Vision with Functional Variational Inference
Eduardo D C Carvalho
R. Clark
Andrea Nicastro
Paul H. J. Kelly
BDL
UQCV
114
22
0
06 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
279
9,136
0
06 Jun 2015
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