Browse by Author Tkatchenko, Alexandre

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Sauceda_etal_BIGDML_2022.pdf.jpg29-Jun-2022BIGDML - Towards accurate quantum machine learning force fields for materialsSauceda, Huziel E.; Sauceda, Huziel E.; Müller, Klaus-Robert; Müller, Klaus-Robert; Tkatchenko, Alexandre; Tkatchenko, Alexandre; Gálvez-González, Luis E.; Gálvez-González, Luis E.; Chmiela, Stefan; Chmiela, Stefan; Paz-Borbón, Lauro Oliver; Paz-Borbón, Lauro Oliver-
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-
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.-
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-
njp13_9_095003.pdf.jpg4-Sep-2013Machine learning of molecular electronic properties in chemical compound spaceMontavon, Grégoire; Rupp, Matthias; Gobre, Vivekanand; Vazquez-Mayagoitia, Alvaro; Hansen, Katja; Tkatchenko, Alexandre; Müller, Klaus-Robert; Lilienfeld, O Anatole von-
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-