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Neural networks and kernel ridge regression for excited states dynamics
  of CH$_2$NH$_2^+$: From single-state to multi-state representations and
  multi-property machine learning models

Neural networks and kernel ridge regression for excited states dynamics of CH2_22​NH2+_2^+2+​: From single-state to multi-state representations and multi-property machine learning models

18 December 2019
Julia Westermayr
Felix A Faber
Anders S. Christensen
O. von Lilienfeld
P. Marquetand
ArXivPDFHTML

Papers citing "Neural networks and kernel ridge regression for excited states dynamics of CH$_2$NH$_2^+$: From single-state to multi-state representations and multi-property machine learning models"

3 / 3 papers shown
Title
Deep Learning for UV Absorption Spectra with SchNarc: First Steps
  Towards Transferability in Chemical Compound Space
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space
Julia Westermayr
P. Marquetand
22
51
0
15 Jul 2020
Machine learning for electronically excited states of molecules
Machine learning for electronically excited states of molecules
Julia Westermayr
P. Marquetand
25
258
0
10 Jul 2020
Representations of molecules and materials for interpolation of
  quantum-mechanical simulations via machine learning
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning
Marcel F. Langer
Alex Goessmann
M. Rupp
AI4CE
23
92
0
26 Mar 2020
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