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S26.06: Transport, dynamics and learning
Time:
Thursday, 21/Mar/2024:
8:30am - 10:30am
Session Chair: Michael Herbst Session Chair: Benjamin Stamm
Location: G22/209 Conference Room 209 in Building 22; size: 40
Presentations
8:30am - 8:50am Learning effective dynamics via kernel-based approximation of Koopman generator
V. Nateghi , F. Nüske
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
8:50am - 9:10am Active, Multi-Fidelity Learning for Efficient Molecular Machine Learning
P. Zaspel
University of Wuppertal
9:10am - 9:30am Artificial Intelligence based detection of local spots in network materials prone to mechanical failure.
B. Bachhav , Z. Wu, B. Markert, F. Bamer
RWTH Aachen University
9:30am - 9:50am Coupling continuum and high fidelity models with multilevel on-the-fly sparse grids
T. Hülser , S. Matera
Fritz-Haber-Institut der Max-Planck-Gesellschaft
