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Regensburg 2022 – wissenschaftliches Programm

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O: Fachverband Oberflächenphysik

O 67: Frontiers of Electronic Structure Theory: Focus on Artificial Intelligence Applied to Real Materials 3

Donnerstag, 8. September 2022, 10:30–12:45, S054

10:30 O 67.1 Quantile Random Forest Model for Extrapolation to the Complete Basis Set Limit in Density Functional Theory Calculations — •Daniel Speckhard, Christian Carbogno, Sven Lubeck, Luca Ghiringhelli, Matthias Scheffler, and Claudia Draxl
10:45 O 67.2 Symmetry and completeness in machine-learning models for atomistic simulations — •Sergey Pozdnyakov and Michele Ceriotti
11:00 O 67.3 Fast, robust, interpretable machine-learning potentialsStephen R. Xie, Richard G. Hennig, and •Matthias Rupp
  11:15 O 67.4 The contribution has been moved to O 58.16.
11:30 O 67.5 Predicting condensed-phase electron densities using machine learning — •Alan Lewis, Andrea Grisafi, Michele Ceriotti, and Mariana Rossi
11:45 O 67.6 Equivariant N-center representations for machine learning molecular Hamiltonians — •Jigyasa Nigam, Michael Willatt, and Michele Ceriotti
12:00 O 67.7 Similarity-of-materials analysis for reusability and interoperability of data in materials databases — •Šimon Gabaj, Martin Kuban, Santiago Rigamonti, and Claudia Draxl
12:15 O 67.8 Supervised and unsupervised deep Learning of topological phase transitions from entanglement aspect for one- and two-dimensional chiral p-wave superconductors — •Ming-Chiang Chung
12:30 O 67.9 Machine Learning the Square-Lattice Ising Model — •Burak Çivitcioğlu, Andreas Honecker, and Rudolf A. Römer
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