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              <p>Dans la lignée des récentes avancées en apprentissage profond de représentations pour le clustering, ce travail (précédemment publié en anglais) présente le modèle DESOM (Deep Embedded SOM), combinant l'apprentisssage non supervisé de représentations et d'une carte auto-organisée de Kohonen (SOM). Le modèle, composé d'un auto-encodeur et d'une couche SOM, est optimisé conjointement, an de régulariser l'espace latent et améliorer la performance de la carte SOM. Nous évaluons les performances de classification et de visualisation ainsi que les bénéfices de l'apprentissage joint. Mots-clef : carte auto-organisée, clustering, apprentissage profond, auto-encodeur.</p>
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