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Number of documents

4

Prof. Sandrine VATON


Experienced Full Professor with a demonstrated history of working in the telecommunications industry.

Skilled in Mathematical Modeling, Network Management, Network Security, Signal Processing and Digital Communications, Statistics, Time Series Analysis and Stochastic Simulations, Software and Hardware Acceleration, Computational Finance.

Strong education professional with a PhD in signal processing from Telecom ParisTech and an accreditation to supervise research (HDR) in computer science from the University of Rennes 1.

Gender equality adviser committed to promote computer science initiatives that reach girls.

Member of the Scientific Council at AFNIC.


Amine Echraibi   

Conference papers2 documents

  • Amine Echraibi, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton. On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models. ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, Jul 2020, Vienna, Austria. ⟨hal-02864385v2⟩
  • Amine Echraibi, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton. An Infinite Multivariate Categorical Mixture Model for Self-Diagnosis of Telecommunication Networks. ICIN 2020 : 23rd Conference on Innovation in Clouds, Internet and Networks, Feb 2020, Paris, France. ⟨10.1109/ICIN48450.2020.9059491⟩. ⟨hal-02431732v2⟩

Preprints, Working Papers, ...2 documents

  • Amine Echraibi, Joachim Cholet, Stéphane Gosselin, Sandrine Vaton. Generalized Stochastic Backpropagation. 2021. ⟨hal-02968975v3⟩
  • Amine Echraibi, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton. Bayesian Mixture Models For Semi-Supervised Clustering. 2019. ⟨hal-02372337⟩