 |
15:00 |
DY 14.1 |
Machine-learned classical density functional theory in higher dimensions with convolutional layers — Felix 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 States — Luca 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
|
|
|