The thirty-fourth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, October 7, 2021.
The theory of optimal transport and the use of Wasserstein distances are attracting increasing attention in statistics and machine learning. At the same time, the definition of sensitivity measures for multivariate responses is a topical research subject. This work examines the construction of probabilistic sensitivity measures using the theory of optimal transport. We obtain a new family of indicators that can deal with multivariate outputs. We test estimators based on alternative algorithmic approaches for computing optimal transport problems, showing promising results and fast execution times for resonable sample sizes.
Joint work with E. Borgonovo & G. Savarè (Bocconi Univ.), A. Figalli (ETH Zürich)
Ref: preprint + code snippets.
Organizing committee: Pierre Barbillon (MIA-Paris), Julien Bect (L2S), Nicolas Bousquet (EDF R&D), Didier Clouteau (MSSMAT), Amélie Fau (LMT), Filippo Gatti (MSSMAT), Bertrand Iooss (EDF R&D), Alexandre Janon (LMO), Sidonie Lefebvre (DOTA), Fernando Lopez-Caballero (MSSMAT), Didier Lucor (LISN), Emmanuel Vazquez (L2S).
Coordinator: Julien Bect (L2S).
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 you 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.