DY 16: Machine Learning in Dynamical Systems and Statistical Physics (joint session DY/BP)
Freitag, 1. Oktober 2021, 11:15–12:30, H2
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11:15 |
DY 16.1 |
Tayloring Reservoir Computing Performance via Delay Time Tuning — •Tobias Hülser, Felix Köster, and Kathy Lüdge
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11:30 |
DY 16.2 |
Employing artificial neural networks to find reaction coordinates and pathways for self-assembly — •Jörn Appeldorn, Arash Nikoubashman, and Thomas Speck
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11:45 |
DY 16.3 |
Efficient Bayesian estimation of the generalized Langevin equation from data — •Clemens Willers and Kamps Oliver
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12:00 |
DY 16.4 |
Master memory function for delay-based reservoir computers — •Felix Köster, Serhiy Yanchuk, and Kathy Lüdge
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12:15 |
DY 16.5 |
Investigating the role of Chaos and characteristic time scales in Reservoir Computing — Marvin Schmidt, Yuriy Mokrousov, Stefan Blügel, Abigail Morrison, and •Daniele Pinna
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