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Semi-supervised novelty detection using ensembles with regularized
  disagreement

Semi-supervised novelty detection using ensembles with regularized disagreement

10 December 2020
A. Tifrea
E. Stavarache
Fanny Yang
    UQCV
ArXivPDFHTML

Papers citing "Semi-supervised novelty detection using ensembles with regularized disagreement"

4 / 4 papers shown
Title
Deep Anti-Regularized Ensembles provide reliable out-of-distribution
  uncertainty quantification
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification
Antoine de Mathelin
Francois Deheeger
Mathilde Mougeot
Nicolas Vayatis
OOD
UQCV
12
2
0
08 Apr 2023
Pathologies of Predictive Diversity in Deep Ensembles
Pathologies of Predictive Diversity in Deep Ensembles
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
John P. Cunningham
UQCV
38
13
0
01 Feb 2023
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