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A Tkatchenko

Showing results (1-10 of 8) with videos related to

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Physical Review Letters|July 16, 2022
Comment on "Dispersion Interaction between Two Hydrogen Atoms in a Static Electric Field"M R Karimpour, D V Fedorov, A Tkatchenko
Zhurnal Nevrologii I Psikhiatrii Imeni S.S. Korsakova|April 21, 2020
[The comparative study of the early stages of sensory and sensory-motor information processing in aggressive and non-aggressive schizophrenic patients]A V Kirenskaya, Z I Storozheva, E A Ilyushina, et al.
Nature Communications|November 16, 2019
Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctionsK T Schütt, M Gastegger, A Tkatchenko, et al.
Journal of Chemical Theory and Computation|July 14, 2024
Accurate Quantum Monte Carlo Forces for Machine-Learned Force Fields: Ethanol as a BenchmarkE Slootman, I Poltavsky, R Shinde, et al.
The Journal of Chemical Physics|July 2, 2018
SchNet - A deep learning architecture for molecules and materialsK T Schütt, H E Sauceda, P-J Kindermans, et al.
Journal of Chemical Theory and Computation|November 28, 2018
SchNetPack: A Deep Learning Toolbox For Atomistic SystemsK T Schütt, P Kessel, M Gastegger, et al.
The Journal of Chemical Physics|April 4, 2020
DFTB+, a software package for efficient approximate density functional theory based atomistic simulationsB Hourahine, B Aradi, V Blum, et al.
The Journal of Chemical Physics|July 22, 2022
Erratum: "DFTB+, a software package for efficient approximate density functional theory based atomistic simulations" [J. Chem. Phys. 152, 124101 (2020)]B Hourahine, B Aradi, V Blum, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Physical Review Letters|July 16, 2022
Comment on "Dispersion Interaction between Two Hydrogen Atoms in a Static Electric Field"M R Karimpour, D V Fedorov, A Tkatchenko
Zhurnal Nevrologii I Psikhiatrii Imeni S.S. Korsakova|April 21, 2020
[The comparative study of the early stages of sensory and sensory-motor information processing in aggressive and non-aggressive schizophrenic patients]A V Kirenskaya, Z I Storozheva, E A Ilyushina, et al.
Nature Communications|November 16, 2019
Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctionsK T Schütt, M Gastegger, A Tkatchenko, et al.
Journal of Chemical Theory and Computation|July 14, 2024
Accurate Quantum Monte Carlo Forces for Machine-Learned Force Fields: Ethanol as a BenchmarkE Slootman, I Poltavsky, R Shinde, et al.
The Journal of Chemical Physics|July 2, 2018
SchNet - A deep learning architecture for molecules and materialsK T Schütt, H E Sauceda, P-J Kindermans, et al.
Journal of Chemical Theory and Computation|November 28, 2018
SchNetPack: A Deep Learning Toolbox For Atomistic SystemsK T Schütt, P Kessel, M Gastegger, et al.
The Journal of Chemical Physics|April 4, 2020
DFTB+, a software package for efficient approximate density functional theory based atomistic simulationsB Hourahine, B Aradi, V Blum, et al.
The Journal of Chemical Physics|July 22, 2022
Erratum: "DFTB+, a software package for efficient approximate density functional theory based atomistic simulations" [J. Chem. Phys. 152, 124101 (2020)]B Hourahine, B Aradi, V Blum, et al.
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