VIRTUAL MEETING: Learning Models from Data: Model Reduction, System Identification and Machine Learning // GAMM Juniors' Summer School on Applied Mathematics and Mechanics

Die Summer School wird als Online-Ereignis stattfinden. Alle Teilnehmerinnen und Teilnehmer erhalten einen Internetzugang zu den Vorträgen, Übungen und Diskussionen.

Objectives and Topics

The aim of this summer school is to study recent developments in the area of learning models from data, which will be presented by three top-level experts in lectures and exercise classes. The combination and interplay of different techniques from physics-based modeling, data-driven modeling, model reduction, system identification and machine learning techniques shall bring together researchers from different disciplines.

In particular, the summer school is tailored for young researchers, i.e. master students in their final phase, PhD students and post-doctoral researchers.

Each participant is invited to present a poster on his/her own research with the emphasis on how learning techniques are used or are intended to be used.

Lecturers

Lectures and exercise courses are given by

• J. Nathan Kutz (University of Washington)
• Benjamin Peherstorfer (New York University)
• Feliks Nüske (Paderborn University)