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On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and
  Conflictual Loss

On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss

16 July 2024
Mohammed Fellaji
Frédéric Pennerath
Brieuc Conan-Guez
Miguel Couceiro
    UQCV
ArXivPDFHTML

Papers citing "On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss"

2 / 2 papers shown
Title
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
268
5,652
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
247
9,109
0
06 Jun 2015
1