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Mathematical modelling in the machine learning era

Science and Information Technology

During this workshop we will discuss the pros and cons of machine learning versus mathematical/statistical models.

Workshop
Date
9 Dec 2020
Time
09:00 - 15:00
Location
Online

Participants
Bernt Wennberg, Chalmers and University of Gothenburg
Philip Gerlee, Chalmers and University of Gothenburg
Robert Feldt, Chalmers
Hitesh Mistry, University of Manchester
Aila Särkkä, Chalmers and University of Gothenburg
Sébastien Benzekry, INRIA Bordeaux - Sud-Ouest
Sandy Anderson, Moffitt Cancer Center
Organizer
Department of Mathematical Sciences

In recent years machine learning and artificial intelligence have been on the rise and progress has been made on problems that previously have been tackled with more traditional mathematical and statistical modelling. Examples of this includes image segmentation, automatic control and medical diagnostics. During this workshop we will discuss the pros and cons of machine learning versus mathematical/statistical models. We will also look at how problem-specific features might affect the choice of method and lastly discuss how the two approaches can be combined within a united modelling framework.​