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Kristof T. Schütt

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SchNetPack 2.0: A neural network toolbox for atomistic machine learning

Dec 11, 2022
Kristof T. Schütt, Stefaan S. P. Hessmann, Niklas W. A. Gebauer, Jonas Lederer, Michael Gastegger

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Automatic Identification of Chemical Moieties

Mar 30, 2022
Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, Oliver T. Unke

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Inverse design of 3d molecular structures with conditional generative neural networks

Sep 10, 2021
Niklas W. A. Gebauer, Michael Gastegger, Stefaan S. P. Hessmann, Klaus-Robert Müller, Kristof T. Schütt

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SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects

May 01, 2021
Oliver T. Unke, Stefan Chmiela, Michael Gastegger, Kristof T. Schütt, Huziel E. Sauceda, Klaus-Robert Müller

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Equivariant message passing for the prediction of tensorial properties and molecular spectra

Feb 08, 2021
Kristof T. Schütt, Oliver T. Unke, Michael Gastegger

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Machine learning of solvent effects on molecular spectra and reactions

Nov 04, 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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XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks

Jun 12, 2020
Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Schütt, Klaus-Robert Müller, Grégoire Montavon

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