Data-driven modeling and analysis
April 26, 2022
The goal of this workshop is to provide an overview of data-driven methods for the analysis of time-series data. Given only measurement or simulation data, these methods can be used to extract global properties of the underlying system such as time scales and metastable sets or to directly learn the governing equations of the system. Other topics of interest include multiscale modeling, homogenization, dimensionality reduction, manifold learning, and control as well as applications in molecular dynamics, fluid dynamics, climate science, and engineering.
The workshop is part of the Thematic Einstein Semester “The Mathematics of Complex Social Systems: Past, Present, and Future”.
Invited Speakers
Nelida Črnjarić-Žic (University of Rijeka)
Alexandre Mauroy (University of Namur)
Marina Meila (University of Washington)
Antonio Navarra (Euro-Mediterranean Center on Climate Change, University of Bologna)
Sebastian Peitz (University of Paderborn)
Konstantinos Zygalakis (University of Edinburgh)
Organizational detail
The workshop takes place as a hybrid event, where the on-site part will be at Zuse Institute Berlin in Berlin-Dahlem.
| Speaker | Title |
|
| 9:00-9:45 | Alexandre Mauroy | Stability analysis in Koopman operator theory: A data-driven approach |
| 9:45-10:30 | Nelida Črnjarić-Žic | The Koopman operator-based data-driven algorithms on nonautonomous and stochastic dynamics |
| 10:30-11:00 | Coffee break | |
| 11:00-11:45 | Sebastian Peitz | Efficient data-driven prediction and control of complex systems via the Koopman operator |
| 11:45-12:30 | Antonio Navarra | Koopman modes of the sea surface temperature in the Tropical Pacific |
| 12:30-14:00 | Lunch break | |
| 14:00-14:45 | Konstantinos Zygalakis | Hybrid modeling for the stochastic simulation of spatial and non-spatial multi-scale chemical kinetics |
| 14:45-15:15 | Luzie Helfmann | Collective variables and tipping analysis of agent-based models |
| 15:15-15:45 | Coffee break | |
| 15:45-16:15 | Kateryna Melnyk | Understanding network dynamics with graph representation learning |
| 16:15-16:45 | Ming Zhong | Machine learning of self organization from observation |
| 16:45-17:00 | Short break | |
| 17:00-17:45 | Marina Meila | Manifold Learning 2.0: Explanations and eigenflows |
Registration
Registration is free of charge. To register for this workshop please use the link:
https://www.conftool.net/tes-summer-2022/
Deadline for registration: April 16, 2022