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On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models

 Amine Echraibi , Joachim Flocon-Cholet , Stéphane Gosselin , Sandrine Vaton
ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, Jul 2020, Vienna, Austria
Communication dans un congrès hal-02864385v2
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Deep Infinite Mixture Models for Fault Discovery in GPON-FTTH Networks

 Amine Echraibi , Joachim Flocon-Cholet , Stephane Gosselin , Sandrine Vaton
IEEE Access, 2021, 9, pp.90488 - 90499. ⟨10.1109/access.2021.3091328⟩
Article dans une revue hal-03394392v1
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Generalized Stochastic Backpropagation

 Amine Echraibi , Joachim Flocon Cholet , Stéphane Gosselin , Sandrine Vaton
Beyond Backpropagation: Novel Ideas for Training Neural Architectures, Workshop at NeurIPS 2020 (2020 Conference on Neural Information Processing Systems), Dec 2020, Virtual Conférence, France
Poster de conférence hal-02968975v3
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An Infinite Multivariate Categorical Mixture Model for Self-Diagnosis of Telecommunication Networks

 Amine Echraibi , Joachim Flocon-Cholet , Stéphane Gosselin , Sandrine Vaton
ICIN 2020 : 23rd Conference on Innovation in Clouds, Internet and Networks, Feb 2020, Paris, France. ⟨10.1109/ICIN48450.2020.9059491⟩
Communication dans un congrès hal-02431732v2
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Bayesian Mixture Models For Semi-Supervised Clustering

 Amine Echraibi , Joachim Flocon-Cholet , Stéphane Gosselin , Sandrine Vaton
2019
Pré-publication, Document de travail hal-02372337v1
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Stochastic Backpropagation through Fourier Transforms

 Amine Echraibi , Joachim Flocon Cholet , Stéphane Gosselin , Sandrine Vaton
29th European Signal Processing Conference (EUSIPCO), Aug 2021, Dublin ( virtual ), Ireland. ⟨10.23919/EUSIPCO54536.2021.9616294⟩
Communication dans un congrès hal-04165289v1
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