Stebėti
Sebastien Röcken
Sebastien Röcken
PhD Student @ TUM
Patvirtintas el. paštas tum.de
Pavadinimas
Cituota
Cituota
Metai
Accurate machine learning force fields via experimental and simulation data fusion
S Röcken, J Zavadlav
npj Computational Materials 10 (1), 69, 2024
112024
chemtrain: Learning deep potential models via automatic differentiation and statistical physics
P Fuchs, S Thaler, S Röcken, J Zavadlav
Computer Physics Communications, 109512, 2025
32025
Predicting solvation free energies with an implicit solvent machine learning potential
S Röcken, AF Burnet, J Zavadlav
The Journal of Chemical Physics 161 (23), 2024
32024
Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements
S Röcken, J Zavadlav
arXiv preprint arXiv:2502.13522, 2025
2025
Accurate machine learning force fields via experimental and simulation data fusion
J Zavadlav, S Röcken
2023
Supplementary Information: Accurate machine learning force fields with experimental and simulation data fusion
S Röcken, J Zavadlav
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Straipsniai 1–6