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Michael Gastegger

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Machine learning of solvent effects on molecular spectra and reactions

Oct 28, 2020
Michael Gastegger, Kristof T. Schütt, Klaus-Robert Müller

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Machine Learning Force Fields

Oct 14, 2020
Oliver T. Unke, Stefan Chmiela, Huziel E. Sauceda, Michael Gastegger, Igor Poltavsky, Kristof T. Schütt, Alexandre Tkatchenko, Klaus-Robert Müller

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Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics

Feb 17, 2020
Julia Westermayr, Michael Gastegger, Philipp Marquetand

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Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Jun 02, 2019
Niklas W. A. Gebauer, Michael Gastegger, Kristof T. Schütt

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Molecular Dynamics with Neural-Network Potentials

Dec 18, 2018
Michael Gastegger, Philipp Marquetand

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Machine learning enables long time scale molecular photodynamics simulations

Nov 22, 2018
Julia Westermayr, Michael Gastegger, Maximilian F. S. J. Menger, Sebastian Mai, Leticia González, Philipp Marquetand

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Generating equilibrium molecules with deep neural networks

Oct 26, 2018
Niklas W. A. Gebauer, Michael Gastegger, Kristof T. Schütt

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Analysis of Atomistic Representations Using Weighted Skip-Connections

Oct 23, 2018
Kim A. Nicoli, Pan Kessel, Michael Gastegger, Kristof T. Schütt

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Quantum-chemical insights from interpretable atomistic neural networks

Jun 27, 2018
Kristof T. Schütt, Michael Gastegger, Alexandre Tkatchenko, Klaus-Robert Müller

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WACSF - Weighted Atom-Centered Symmetry Functions as Descriptors in Machine Learning Potentials

Dec 15, 2017
Michael Gastegger, Ludwig Schwiedrzik, Marius Bittermann, Florian Berzsenyi, Philipp Marquetand

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