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A view on model misspecification in uncertainty quantification

A view on model misspecification in uncertainty quantification

30 October 2022
Yuko Kato
David Tax
Marco Loog
ArXivPDFHTML

Papers citing "A view on model misspecification in uncertainty quantification"

4 / 4 papers shown
Title
Ensemble-based Uncertainty Quantification: Bayesian versus Credal
  Inference
Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference
M. Shaker
Eyke Hüllermeier
UD
UQCV
PER
BDL
227
16
0
21 Jul 2021
DEUP: Direct Epistemic Uncertainty Prediction
DEUP: Direct Epistemic Uncertainty Prediction
Salem Lahlou
Moksh Jain
Hadi Nekoei
V. Butoi
Paul Bertin
Jarrid Rector-Brooks
Maksym Korablyov
Yoshua Bengio
PER
UQLM
UQCV
UD
200
81
0
16 Feb 2021
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
270
5,660
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
282
9,136
0
06 Jun 2015
1