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Wednesday, May 29, 2024
| Time | Event | (+) |
| 13:30 - 14:30 | Data assimilation and ML - Marc Bocquet | |
| 14:30 - 15:30 | Assisting sampling of physical systems and Bayesian Inference with generative models - Marylou Gabrié | |
| 15:30 - 16:00 | Coffee break | |
| 16:00 - 17:00 | Inferring effective state variables and dynamics from data - Nicolas Brodu | |
| 17:00 - 18:00 | Simulation-based inference for the Physical Sciences - Gilles Louppe | |
| 18:00 - 20:00 | Wine & cheese with a poster session |
Thursday, May 30, 2024
| Time | Event | (+) |
| 08:30 - 09:00 | Welcoming coffee | |
| 09:00 - 10:00 | Scientific machine learning - Chris Rackauckas | |
| 10:00 - 11:00 | An overview of operator learning - Nicolas Boullé | |
| 11:00 - 11:30 | Coffee break | |
| 11:30 - 12:30 | End-to-end neural data assimilation - Ronan Fablet | |
| 12:30 - 14:00 | Lunch break with a poster session | |
| 14:00 - 15:00 | Physics Informed Neural Networks: Some Insights and Limitations - Emmanuel de Bézenac | |
| 15:00 - 16:00 | Neural ODEs, neural operators, and their efficiency - Julia Gusak | |
| 16:00 - 16:30 | Coffee break | |
| 16:30 - 17:30 | Learning Time Integration for Long-term Dynamics - David Greenberg |
Friday, May 31, 2024
| Time | Event | (+) |
| 09:00 - 12:00 | Hands-on session on SciML with Julia - Chris Rackauckas |
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