Browse by Author Gastegger, Michael

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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-
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.-
Gebauer_etal_Inverse_2022.pdf.jpg21-Feb-2022Inverse design of 3d molecular structures with conditional generative neural networksGebauer, Niklas W. A.; Gastegger, Michael; Hessmann, Stefaan S. P.; Müller, Klaus-Robert; Schütt, Kristof T.-
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-
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-
Gastegger_etal_Machine_2021.pdf.jpg23-Jul-2021Machine learning of solvent effects on molecular spectra and reactionsGastegger, Michael; Schütt, Kristof T.; Müller, Klaus-Robert-
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-
Westermayr_etal_Perspective_2021.pdf.jpg21-Jun-2021Perspective on integrating machine learning into computational chemistry and materials scienceWestermayr, Julia; Gastegger, Michael; Schütt, Kristof T.; Maurer, Reinhard J.-
schuett_etal_2019.pdf.jpg10-Sep-2019Quantum-Chemical Insights from Interpretable Atomistic Neural NetworksSchütt, Kristof T.; Gastegger, Michael; Tkatchenko, Alexandre; Müller, Klaus-Robert-
est_4_2_023004.pdf.jpg19-Aug-2022Roadmap on Machine learning in electronic structureKulik, Heather J.; Hammerschmidt, Thomas; Schmidt, J.; Botti, Silvana; Marques, Miguel A. L.; Boley, M.; Scheffler, M.; Todorović, Milica; Rinke, Patrick; Oses, Corey; Smolyanyuk, Andriy; Curtarolo, Stefano; Tkatchenko, A.; Bartók, Albert P.; Manzhos, Sergei; Ihara, M.; Carrington, Tucker; Behler, Jörg; Isayev, Olexandr; Veit, Max; Grisafi, Andrea; Nigam, Jigyasa; Ceriotti, Michele; Schütt, Kristof T.; Westermayr, Julia; Gastegger, Michael; Maurer, Reinhard J.; Kalita, B.; Burke, Kieron; Nagai, R.; Akashi, R.; Sugino, O.; Hermann, J.; Noé, Frank; Pilati, Sebastiano; Draxl, Claudia; Kuban, M.; Rigamonti, S.; Scheidgen, M.; Esters, Marco; Hicks, David; Toher, Cormac; Balachandran, Prasanna Venkataraman; Tamblyn, Isaac; Whitelam, S.; Bellinger, C.; Ghiringhelli, Luca M.-
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-