Methodological and theoretical advances in Physics-Informed Machine Learning>

Planning

Wednesday, April 15, 2026
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
›9:00 (30min)
Welcome
›9:30 (50min)
Reinforcement learning
› Amphi A0.04
›10:20 (30min)
Coffee break
› Sortie A0.04
›10:50 (50min)
Optimisation
› Amphi A0.04
›11:40 (50min)
Numerical methods
› Amphi A0.04
›12:30 (1h30)
Lunch
› Canopée
›14:00 (50min)
Generative models
› Amphi A0.04
›14:50 (50min)
Optimal control
› Amphi A0.04
›15:40 (30min)
Coffee break
› Sortie A0.04
›16:10 (50min)
Inverse problems
› Amphi A0.04
›17:00 (1h30)
Poster Session
Poster Session
› Sortie A0.04
Session
Speech/Intervention
Logistics
Break
Tour
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