Geodesic
Bayes in action in deep learning and dictionary learning
Julyan Arbel1 ; Hong-Phuong Dang2 ; Clement Elvira3 ; Cedric Herzet4 ; Zacharie Naulet5 ; Mariia Vladimirova1
1 Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
2 LaTIM, INSERM-UMR1101, Univ. de Bretagne Occidentale, Brest, & ECAM Rennes, Louis de Broglie, Bruz, France
3 IETR UMR CNRS 6164, CentraleSupelec Rennes Campus 35576 Cesson Sévigné, France
4 Inria centre Rennes - Bretagne Atlantique, Rennes, France
5 Université Paris-Saclay, CNRS, Laboratoire de mathématiques d’Orsay, 91405, Orsay, France
ESAIM. Proceedings, Tome 74 (2023), pp. 90-107.

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This article summarizes some recent works and associated challenges in the field of Bayesian statistics that were presented during the Journées MAS 2020. The goal of the session was to give an overview of the many aspects of Bayesian statistics investigated by young researchers of the community.
DOI : 10.1051/proc/202374090

Julyan Arbel 1 ; Hong-Phuong Dang 2 ; Clement Elvira 3 ; Cedric Herzet 4 ; Zacharie Naulet 5 ; Mariia Vladimirova 1

1 Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
2 LaTIM, INSERM-UMR1101, Univ. de Bretagne Occidentale, Brest, & ECAM Rennes, Louis de Broglie, Bruz, France
3 IETR UMR CNRS 6164, CentraleSupelec Rennes Campus 35576 Cesson Sévigné, France
4 Inria centre Rennes - Bretagne Atlantique, Rennes, France
5 Université Paris-Saclay, CNRS, Laboratoire de mathématiques d’Orsay, 91405, Orsay, France 
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     author = {Julyan Arbel and Hong-Phuong Dang and Clement Elvira and Cedric Herzet and Zacharie Naulet and Mariia Vladimirova},
     title = {Bayes in action in deep learning and dictionary learning},
     journal = {ESAIM. Proceedings},
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     doi = {10.1051/proc/202374090},
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Julyan Arbel; Hong-Phuong Dang; Clement Elvira; Cedric Herzet; Zacharie Naulet; Mariia Vladimirova. Bayes in action in deep learning and dictionary learning. ESAIM. Proceedings, Tome 74 (2023), pp. 90-107. doi : 10.1051/proc/202374090. http://geodesic.mathdoc.fr/articles/10.1051/proc/202374090/

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