Regensburg 2022 – wissenschaftliches Programm

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O: Fachverband Oberflächenphysik

O 83: Frontiers of Electronic Structure Theory: Focus on Artificial Intelligence Applied to Real Materials 4

Freitag, 9. September 2022, 10:30–13:00, S054

  10:30 O 83.1 The contribution has been moved to MM 20.7.
10:45 O 83.2 Stacking the odds: Distribution-biased generative deep learning for molecular design — •Joe Gilkes, Julia Westermayr, Rhyan Barrett, and Reinhard J. Maurer
11:00 O 83.3 Machine learning TCP phases with domain knowledge of the interatomic bond — •Mariano Forti, Alesya Burakovskaya, Ralf Drautz, and Thomas Hammerschmidt
11:15 O 83.4 Ab initio random structure search of organic molecules at substrates — •Dmitrii Maksimov and Mariana Rossi
11:30 O 83.5 Active learning and element-embedding approach in neural networks for infinite-layer versus perovskite oxidesArmin Sahinovic and •Benjamin Geisler
11:45 O 83.6 Indirect learning interatomic potential models for accelerated materials simulations — •Joe D. Morrow and Volker L. Deringer
12:00 O 83.7 Predicting hot electrons free energies from ground-state data — •Chiheb Ben Mahmoud, Federico Grasselli, and Michele Ceriotti
  12:15 O 83.8 The contribution has been withdrawn.
12:30 O 83.9 MD-based Raman Spectra using Machine Learning — •Manuel Grumet, Karin S. Thalmann, Tomáš Bučko, and David A. Egger
12:45 O 83.10 Thermal Transport via Green-Kubo Method and Message-Passing Neural-Network PotentialsMarcel F. Langer, Florian Knoop, Christian Carbogno, Matthias Scheffler, and •Matthias Rupp
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