Évènements / Séminaires

Évènements à venir

The Smart Energy System Simulation and Control Center of the Energy Lab@KIT: an open research platform for automation and control

Thursday 14th November 2024 at 2:30pm, in Salle Hooper, 3rd floor at IBM building, 14 Rue Jean Rostand, 91400 Orsay Speakers: Veit Hagenmeyer, Professor of Energy Informatics with the Faculty of Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany Title: The Smart Energy System Simulation and Control Center of the Energy Lab@KIT: an open research platform for automation […]

14/11/2024

UQSay #77

The seventy-seventh UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, October 31, 2024. 2–3 PM — Nadège Polette (Mines Paris PSL – CEA DAM DIF) — [slides] Mitigating Overconfidence in Bayesian Field Inversion thanks to Hyperparameters Sampling The objective of Bayesian field inversion is to approximate the posterior […]

31/10/2024

Talk by Liang Zheng »The many meanings with image pairs »

The seminar will take place at CentraleSupelec on Friday, September 27, at 10:00 AM in Amphi VI, located in the Eiffel building of CentraleSupelec.  Title: The many meanings with image pairs Abstract: Training AI models with image pairs has been studied for a long time and proven very useful. In this talk, I will first revisit […]

27/10/2024

UQSay #76

The seventy-sixth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, October 17, 2024. 4–5 PM — Habib Najm (Sandia National Laboratories) — [slides] Uncertainty Quantification in Computational Combustion Models Uncertainty quantification (UQ) in large scale computational combustion models faces key challenges of high dimensionality and computational cost. These […]

17/10/2024

UQSay #75

The seventy-fifth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, October 3, 2024. 2–3 PM — Olivier Laurent (SATIE, Université Paris-Saclay – U2IS, ENSTA) — [slides] A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors The distribution of modern deep neural networks (DNNs) weights — crucial for uncertainty quantification […]

03/10/2024