Speaker:
James A. Nichols
Affiliation:
Laboratoire Jacques-Louis Lions, UPMC, Sorbonnes Universités, Paris, France
Date:
Tue, 05/03/2019 - 11:05am
Venue:
RC-4082, The Red Centre, UNSW
Abstract:
Reduced (or surrogate) modelling replaces a high-resolution PDE model with some simple model that only loses some small and known accuracy. Reduced models are designed to allow for fast or closed-form computation, opening the door for uncertainty quantification, inverse problems, or data assimilation and more.
I will present recent work in reduced models, including a discussion about worst-case versus average-case error optimisation, some results in optimal linear reduced models, and experiments in non-linear models.