Monday, October 30, 2023

UQSay #64

The sixty-fourth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, November 2, 2023.

2–3 PM — Christoph Molnar & Timo Freiesleben (Machine Learning in Science Cluster, University of Tübingen.) — [slides]

Supervised Machine Learning in Science

From folding proteins and predicting tornadoes to studying human nature — machine learning has changed science. Science always had an intimate relationship with prediction, but machine learning intensifies this focus. Can this hyper-focus on prediction models be justified? Can a machine learning model be part of a scientific model? Or are we on the wrong track? We explore and justify the use of supervised machine learning in science. However, a pure and naive application of supervised learning won't get you far, because raw machine learning has so many insufficiencies that make it unusable in this form for science. Unintelligible models, lack of uncertainty quantification, lack of causality. But we already have all the puzzle pieces to fix machine learning, from incorporating domain knowledge and assuring the representativeness of the training data to robust, interpretable, and causal models. We bring together the philosophical justification and the solutions that make supervised machine learning a powerful tool for science.

Organizing committee: Pierre Barbillon (MIA-Paris), Julien Bect (L2S), Nicolas Bousquet (EDF R&D), Amélie Fau (LMPS), Filippo Gatti (LMPS), Bertrand Iooss (EDF R&D), Alexandre Janon (LMO), Sidonie Lefebvre (ONERA), Didier Lucor (LISN), Emmanuel Vazquez (L2S).

Coordinators: Julien Bect (L2S) & Sidonie Lefebvre (ONERA)

Practical details: the seminar will be held online using Microsoft Teams.

If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay group on Teams, simply send an email and you will be invited. Please specify which email address the invitation must be sent to (this has to be the address associated with your Teams account).

You will find the link to the seminar on the "General" UQSay channel on Teams, approximately 15 minutes before the beginning.

The technical side of things: you can use Teams either directly from your web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.