The goal of this school is to develop the skills of researchers and engineers in the domain of uncertainty management of computer codes.

Some of the lectures will be followed by practical computer works. Collaborative works, round tables and poster sessions will promote exchanges between participants.

The prerequisites to possess are the mathematical bases of the uncertainty quantification science.

LECTURERS

Sébastien Da Veiga (Safran): Advanced methods in sensitivity analysis

Stéphane Gaiffas (Ecole Polytechnique): Methods for covariance matrix estimation 

Tim Sullivan (Free University of Berlin / Zuse Institute Berlin): Optimal distributionally robust uncertainty quantification

Nicolas Vayatis (CMLA, ENS Cachan): Scoring and machine learning