09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
›9:00 (30min)
9:00 - 9:30 (30min)
Accueil A0.04
9:30 - 10:20 (50min)
Apprentissage par renforcement
Amphi A0.04
› Moving from optimal control to continuous-time reinforcement learning using PINNs
- Alena Shilova, Centre Inria de Saclay
09:30-10:20 (50min)
10:20 - 10:50 (30min)
Pause café
Sortie A0.04
10:50 - 11:40 (50min)
Optimisation
Amphi A0.04
› Bridging Physics and Learning: An Optimization Framework for Hybrid Differentiable Models
- Jordan Patracone, Université Jean Monnet - Saint-Étienne
10:50-11:40 (50min)
11:40 - 12:30 (50min)
Méthodes numériques
Amphi A0.04
12:30 - 14:00 (1h30)
Déjeuner
Canopée
14:00 - 14:50 (50min)
Modèles génératifs
Amphi A0.04
› Propagating Uncertainty in Stochastic Differential Equations with Neural Solvers of the Fokker Planck Equation
- Lucas Drumetz, IMT Atlantique
14:00-14:50 (50min)
14:50 - 15:40 (50min)
Contrôle optimal
Amphi A0.04
› An optimal control problem on a data-driven reduced model in epidemiology
- Clémentine Courtès, Institut de Recherche Mathématique Avancée
14:50-15:40 (50min)
15:40 - 16:10 (30min)
Pause café
Sortie A0.04
16:10 - 17:00 (50min)
Problèmes inverses
Amphi A0.04
› An optimal control problem on a data-driven reduced model in epidemiology
- Arnaud Vadeboncoeur, Cambridge University
16:10-17:00 (50min)
17:00 - 18:30 (1h30)
Poster Session
Sortie A0.04
Poster Session
