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Events

Upcomming events

UQSay #39

The thirty-ninth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, December 16, 2021. 2–3 PM — Gianni Franchi (U2IS, ENSTA Paris) — [slides] Encoding the latent posterior of Bayesian neural networks for Uncertainty Quantification Bayesian neural networks (BNNs) have been long considered an ideal, yet unscalable solution for […]

16/12/2021

AVIS DE SOUTENANCE HDR Giorgio VALMORBIDA

Enseignant-Chercheur à CentraleSupélec, L2S, soutiendra son mémoire en vue de l’obtention de l’Habilitation à Diriger des Recherches de l’Université Paris-Saclay  “Semidefinite Programming Methods for the Stability Analysis of Nonlinear Systems”  Le jeudi 9 décembre 2021 à 14h30 Lieu : Amphi III, Bâtiment Eiffel à CentraleSupélec  Pour la participation à distance :  https://cnrs.zoom.us/j/98146270393?pwd=eExKOW5zeFdOaW9Cc0dpZHB2T3lzUT09  Membres du jury […]

09/12/2021

Séminaire de Lucas Brivadis

14h00-15h00 – Online Infinite-dimensional Luenberger observers: application to a crystallization process Lucas Brivadis (LAGEPP, Université Lyon 1) Abstract. During a crystallization process, the Particle Size Distribution (PSD) is a relevant information that needs to be estimated through other measurements, such as the Chord Length Distribution (CLD). The PSD-to-CLD mapping depends on particle geometry. We propose […]

06/12/2021

NeurIPS | 2021 – Prof. Pablo Piantanida and Dr. Marco Romanelli

DOCTOR: A Simple Method for Detecting Misclassification Errors  was awarded a Spotlight Presentation at NeurIPS 2021, being one of the top papers presented to the world-leading AI conference. This year saw a record-breaking number of submissions, with a total of 9122 full paper submissions. From these, only 26% were accepted for presentation at the conference.  Less than 3% were accepted as spotlights.  The […]

06/12/2021

UQSay #38

The thirty-eighth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, December 2, 2021. 2–3 PM — Luc Pronzato (CNRS, Univ. Côte d’Azur) — [slides] Maximum Mean Discrepancy, Bayesian integration and kernel herding for space-filling design A standard objective in computer experiments is to predict/interpolate the behaviour of an […]

02/12/2021