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Berlin 2024 – wissenschaftliches Programm

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SOE: Fachverband Physik sozio-ökonomischer Systeme

SOE 8: Machine Learning in Dynamics and Statistical Physics II (joint session DY/SOE)

Dienstag, 19. März 2024, 09:30–13:00, BH-N 243

09:30 SOE 8.1 Pareto-Based Selection of Data-Driven Ordinary Differential Equations — •Gianmarco Ducci, Karsten Reuter, and Christoph Scheurer
09:45 SOE 8.2 Accurate Memory Kernel Extraction from Discretized Time-Series Data — •Lucas Tepper
10:00 SOE 8.3 Coarse-graining non-equilibrium systems with machine learning: from conceptual challenges to new approaches — •Patrick Egenlauf and Miriam Klopotek
10:15 SOE 8.4 Statistical criteria for the prediction of dynamical clustering in granular gases — •Sai Preetham Sata, Dmitry Puzyrev, and Ralf Stannarius
10:30 SOE 8.5 Excitability and Memory in a Time-Delayed Optoelectronic Neuron — •Jonas Mayer Martins, Svetlana V. Gurevich, and Julien Javaloyes
10:45 SOE 8.6 Anisotropic diffusion analysis in confined geometries — •Kevin Höllring, Andreas Baer, Nataša Vučemilović-Alagić, David M. Smith, and Ana-Sunčana Smith
11:00 SOE 8.7 Data assimilation of cardiac dynamics by means of adjoint optimization — •Inga Kottlarz, Sebastian Herzog, Patrick Vogt, Stefan Luther, and Ulrich Parlitz
  11:15 15 min. break
11:30 SOE 8.8 Collective Variables for Neural Networks — •Konstantin Nikolaou, Samuel Tovey, Sven Krippendorf, and Christian Holm
11:45 SOE 8.9 Fluctuating weight dynamics and loss landscape in deep linear networks — •Markus Gross
12:00 SOE 8.10 Loss is More: Exploring the weight space of a perceptron via enhanced sampling techniques — •Margherita Mele, Roberto Menichetti, Alessandro Ingrosso, and Raffaello Potestio
12:15 SOE 8.11 Emergent oscillating dimensionality transformations in deep learning — •Pascal de Jong, Felix J. Meigel, and Steffen Rulands
12:30 SOE 8.12 Investigating the Evolution of Fisher Information for Neural Network Dynamics — •Marc Sauter, Samuel Tovey, Konstantin Nikolaou, and Christian Holm
12:45 SOE 8.13 Near-zero-cost post-training uncertainties for deep learning architectures — •Filippo Bigi, Sanggyu Chong, Michele Ceriotti, and Federico Grasselli
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DPG-Physik > DPG-Verhandlungen > 2024 > Berlin