Browse by Author Chmiela, Stefan

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PreviewIssue DateTitleAuthor(s)Editor(s)
Keith_etal_Combining_2021.pdf.jpg7-Jul-2021Combining machine learning and computational chemistry for predictive insights into chemical systemsKeith, John A.; Vassilev-Galindo, Valentin; Cheng, Bingqing; Chmiela, Stefan; Gastegger, Michael; Müller, Klaus-Robert; Tkatchenko, Alexandre-
Sauceda_etal_Dynamical_2020.pdf.jpg19-Jan-2021Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperatureSauceda, Huziel E.; Vassilev-Galindo, Valentin; Chmiela, Stefan; Müller, Klaus-Robert; Tkatchenko, Alexandre-
Unke_etal_Machine_2021.pdf.jpg11-Mar-2021Machine learning force fieldsUnke, Oliver T.; Chmiela, Stefan; Sauceda, Huziel E.; Gastegger, Michael; Poltavsky, Igor; Schütt, Kristof T.; Tkatchenko, Alexandre; Müller, Klaus-Robert-
e1603015.full.pdf.jpg2017Machine learning of accurate energy-conserving molecular force fieldsChmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E.; Poltavsky, Igor; Schütt, Kristof T.; Müller, Klaus-Robert-
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-
Unke_etal_SpookNet_2021.pdf.jpg14-Dec-2021SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effectsUnke, Oliver T.; Chmiela, Stefan; Gastegger, Michael; Schütt, Kristof T.; Sauceda, Huziel E.; Müller, Klaus-Robert-
chmiela_stefan.pdf.jpg2019Towards exact molecular dynamics simulations with invariant machine-learned modelsChmiela, Stefan-