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Items: 5

1.

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions.

Schütt KT, Gastegger M, Tkatchenko A, Müller KR, Maurer RJ.

Nat Commun. 2019 Nov 15;10(1):5024. doi: 10.1038/s41467-019-12875-2.

2.

SchNetPack: A Deep Learning Toolbox For Atomistic Systems.

Schütt KT, Kessel P, Gastegger M, Nicoli KA, Tkatchenko A, Müller KR.

J Chem Theory Comput. 2019 Jan 8;15(1):448-455. doi: 10.1021/acs.jctc.8b00908. Epub 2018 Dec 10.

PMID:
30481453
3.

SchNet - A deep learning architecture for molecules and materials.

Schütt KT, Sauceda HE, Kindermans PJ, Tkatchenko A, Müller KR.

J Chem Phys. 2018 Jun 28;148(24):241722. doi: 10.1063/1.5019779.

PMID:
29960322
4.

Machine learning of accurate energy-conserving molecular force fields.

Chmiela S, Tkatchenko A, Sauceda HE, Poltavsky I, Schütt KT, Müller KR.

Sci Adv. 2017 May 5;3(5):e1603015. doi: 10.1126/sciadv.1603015. eCollection 2017 May.

5.

Quantum-chemical insights from deep tensor neural networks.

Schütt KT, Arbabzadah F, Chmiela S, Müller KR, Tkatchenko A.

Nat Commun. 2017 Jan 9;8:13890. doi: 10.1038/ncomms13890.

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