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Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty
  Modeling

Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling

2 February 2023
Lucas Berry
D. Meger
ArXivPDFHTML

Papers citing "Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling"

6 / 6 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
Local Flow Matching Generative Models
Local Flow Matching Generative Models
Chen Xu
Xiuyuan Cheng
Yao Xie
44
0
0
03 Jan 2025
Understanding Failures in Out-of-Distribution Detection with Deep
  Generative Models
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily H. Zhang
Mark Goldstein
Rajesh Ranganath
OODD
143
103
0
14 Jul 2021
Cubic-Spline Flows
Cubic-Spline Flows
Conor Durkan
Artur Bekasov
Iain Murray
George Papamakarios
TPM
48
57
0
05 Jun 2019
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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