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DY: Fachverband Dynamik und Statistische Physik

DY 14: Machine Learning in Dynamics and Statistical Physics II

Montag, 9. März 2026, 15:00–18:30, HÜL/S186

15:00 DY 14.1 Machine-learned classical density functional theory in higher dimensions with convolutional layersFelix Glitsch, Jens Weimar, and •Martin Oettel
15:15 DY 14.2 Scalable Boltzmann Generators for equilibrium sampling of large-scale materials — •Maximilian Schebek, Frank Noé, and Jutta Rogal
15:30 DY 14.3 Autoencoder Learning Dynamics on MCMC Ising Dataset — •Max Weinmann and Miriam Klopotek
15:45 DY 14.4 Learning order: can neural networks discover phase transitions without symmetry functions? — •Carina Karner
16:00 DY 14.5 Microscopy on Autopilot: Self-Supervised Transformers for Feature Detection and Control — •Damián Baláž, Gianmarco Ducci, Christoph Scheurer, Karsten Reuter, and Hendrik H. Heenen
16:15 DY 14.6 Learning microstructure in active matter — •Writu Dasgupta, Suvendu Mandal, Aritra Mukhopadhyay, and Benno Liebchen
16:30 DY 14.7 Physical embodiment enabled learning for autonomous navigation of active particles in complex flow fields — •Diptabrata Paul, Nikola Milosevic, Nico Scherf, and Frank Cichos
  16:45 15 min. break
17:00 DY 14.8 Machine Learning for Electric-Field Driven Nuclear Dynamics in Solids and Liquids — •Elia Stocco, Christian Carbogno, and Mariana Rossi
17:15 DY 14.9 Machine-learned Potentials for Vibrational Properties of Acene-based Molecular Crystals — •Shubham Sharma, Burak Gurlek, Paolo Lazzaroni, and Mariana Rossi
17:30 DY 14.10 Spin-phonon systems in the age of modern atomistic simulations — •Ilija Srpak, Michael J. Willatt, Stuart C. Althorpe, and Ali Alavi
17:45 DY 14.11 Self-Consistent Benchmarking of Machine Learning Force Fields via Energy-Landscape Exploration — •Anand Sharma, Igor Poltavskyi, and Alexandre Tkatchenko
18:00 DY 14.12 Solving Classical and Quantum spin glasses with Deep Boltzman Quantum StatesLuca Leone, •Arka Dutta, Markus Heyl, Enrico Prati, and Pietro Torta
18:15 DY 14.13 Optimization and Representability of time-dependent Neural Quantum States: a study of the 1D critical quantum Ising model — •Wladislaw Krinitsin, Mohammad Abedi, Jonas Rigo, and Markus Schmitt
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