Towards a better understanding of deep neural networks representations using deep generative networks
2017
Détails
Titre
Towards a better understanding of deep neural networks representations using deep generative networks
Auteur(s)/ trice(s)
Despraz, Jérémie (School of Management and Engineering Vaud, HES-SO University of Applied Sciences Western Switzerland ; SIB Swiss Intitute of Bioinformatics, Lausanne, Switzerland)
Gomez Schnyder, Stéphane (School of Management and Engineering Vaud, HES-SO University of Applied Sciences Western Switzerland ; SIB Swiss Intitute of Bioinformatics, Lausanne, Switzerland)
Satizábal, Héctor F. (School of Engineering and Management Vaud, HES-SO, University of Applied Sciences and Arts Western Switzerland)
Peña-Reyes, Carlos Andrés (School of Management and Engineering Vaud, HES-SO University of Applied Sciences Western Switzerland ; SIB Swiss Intitute of Bioinformatics, Lausanne, Switzerland)
Gomez Schnyder, Stéphane (School of Management and Engineering Vaud, HES-SO University of Applied Sciences Western Switzerland ; SIB Swiss Intitute of Bioinformatics, Lausanne, Switzerland)
Satizábal, Héctor F. (School of Engineering and Management Vaud, HES-SO, University of Applied Sciences and Arts Western Switzerland)
Peña-Reyes, Carlos Andrés (School of Management and Engineering Vaud, HES-SO University of Applied Sciences Western Switzerland ; SIB Swiss Intitute of Bioinformatics, Lausanne, Switzerland)
Date
2017-11
Publié dans
Proceedings of the 9th International Joint Conference on Computational Intelligence, 1-3 November 2017, Funchal, Madeira, Portugal
Editeur
Funchal, Madeira, Portugal, 1-3 November 2017
Pagination
8 p.
Présenté à
Proceedings of the 9th International Joint Conference on Computational Intelligence, Funchal, Madeira, Portugal, 2017-11-01, 2017-11-03
ISBN
978-989-758-274-5
Type de papier
full paper
Domaine
Ingénierie et Architecture
Ecole
HEIG-VD
Institut
IICT - Institut des Technologies de l'Information et de la Communication
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Documents de conférences
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