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DFG-GRK 2297: Research Training Group Mathematical Complexity Reduction
Time:
Tuesday, 19/Mar/2024:
2:00pm - 4:00pm
Session Chair: Jan Heiland Session Chair: Feliks Nüske Session Chair: Thomas Richter
Location:G22/020
Conference Room 020 in Building 22; size: 70
Different concepts of complexity reduction will be presented, spanning from model order reduction over adaptive numerical schemes to refined sparsity exploiting approaches to polynomial optimization.
Session Abstract
Different concepts of complexity reduction will be presented, spanning from model order reduction over adaptive numerical schemes to refined sparsity exploiting approaches to polynomial optimization.
Presentations
2:00pm - 2:20pm
Bi-linear Control Based On gEDMD for Metastable Systems
L. Guo, F. Nüske, J. Heiland
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
2:20pm - 2:40pm
Smooth clustering-based autoencoders for very low-dimensional parametrizations of fluid flow models
J. Heiland1,2, Y. Kim1,2
1Otto von Guericke University Magdeburg; 2Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
2:40pm - 3:00pm
Physics-based, non-intrusive modeling for systems with spatially localized behavior through reduced/full-order model coupling
L. Gkimisis1, N. Aretz3, M. Tezzele3, P. Benner1,2, T. Richter2, K. E. Willcox3
1Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg; 2Otto von Guericke University Magdeburg; 3The University of Texas at Austin, USA
3:00pm - 3:20pm
Error analysis for hybrid finite element/neural network discretizations
