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Winner-takes-all learners are geometry-aware conditional density
  estimators

Winner-takes-all learners are geometry-aware conditional density estimators

7 June 2024
Victor Letzelter
David Perera
Cédric Rommel
Mathieu Fontaine
S. Essid
Gael Richard
Patrick Pérez
ArXivPDFHTML

Papers citing "Winner-takes-all learners are geometry-aware conditional density estimators"

3 / 3 papers shown
Title
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
David Perera
Victor Letzelter
Théo Mariotte
Adrien Cortés
Mickaël Chen
S. Essid
Ga¨el Richard
74
2
0
20 Jan 2025
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
1