Browse by Author Gastegger, Michael

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PreviewIssue DateTitleAuthor(s)Editor(s)
acs.jpclett.0c00527.pdf.jpg20-Apr-2020Combining SchNet and SHARC: The SchNarc Machine Learning Approach for Excited-State DynamicsWestermayr, Julia; Gastegger, Michael; Marquetand, Philipp-
26-Jul-2021Datasets: Machine learning of solvent effects on molecular spectra and reactionsGastegger, Michael; Schütt, Kristof T.; Müller, Klaus-Robert-
Gastegger_etal_2019.pdf.jpg14-Dec-2018Exploring density functional subspaces with genetic algorithmsGastegger, Michael; González, Leticia; Marquetand, Philipp-
25-Sep-2019Hamiltonian datasets: "Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions""Schütt, Kristof T.; Gastegger, Michael; Tkatchenko, Alexandre; Müller, Klaus-Robert; Maurer, Reinhard J.-
c9sc01742a.pdf.jpg5-Aug-2019Machine learning enables long time scale molecular photodynamics simulationsWestermayr, Julia; Gastegger, Michael; Menger, Maximilian F. S. J.; Mai, Sebastian; González, Leticia; Marquetand, Philipp-
gastegger_marquetand_2020.pdf.jpg4-Jun-2020Molecular Dynamics with Neural Network PotentialsGastegger, Michael; Marquetand, Philipp-
sauceda_etal_2020.pdf.jpg24-Sep-2020Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fieldsSauceda, Huziel E.; Gastegger, Michael; Chmiela, Stefan; Müller, Klaus-Robert; Tkatchenko, Alexandre-
schuett_etal_2019.pdf.jpg10-Sep-2019Quantum-Chemical Insights from Interpretable Atomistic Neural NetworksSchütt, Kristof T.; Gastegger, Michael; Tkatchenko, Alexandre; Müller, Klaus-Robert-