Program

The goal of this event is to gather scientists to work and discuss on Scientific Machine Learning. It will take place in Strasbourg University, France. It runs from 2pm on Monday, July 8th to 12pm on Friday, July 12th, 2024. A detailed schedule is available here.

Scientific Machine Learning

Scientific Machine Learning (SciML) is a relatively new research field based on both machine learning (ML) and scientific computing tools. Its aim is the development of new methods to solve several kinds of problems, which can be forward multidimensional partial differential equations, identification of parameters, or inverse problems. The methods we seek must be robust, reliable and interpretable. The new SciML tools allow the natural inclusion of data in the numerical simulation in order to generate new results. This new methodology will be at the forefront of the next wave of data-driven scientific discovery in the physical and engineering sciences. More precisely, our goals are:

• to introduce the mathematical concepts lying at the foundation of machine learning as used in scientific computing;
• to give an overview of the different approaches developed to address these problems;
• to give insight on the latest numerical tools in scientific machine learning and data inclusion for the solution of PDEs.

Call for posters

Do not hesitate to contact us at sciml24@math.unistra.fr if you wish to apply to present a poster.

Organizing committee

Bruno Després (Sorbonne Université, Paris, France)
Victorita Dolean (TU Eindhoven, the Netherlands)
Emmanuel Franck (Inria, Strasbourg, France)
Stéphane Lanteri (Inria, Nice, France)
Victor Michel-Dansac (Inria, Strasbourg, France)
Laurent Navoret (Inria, Strasbourg, France)