Machine learning and excited-state molecular dynamics

28 May 2020

Papers citing "Machine learning and excited-state molecular dynamics"

6 / 6 papers shown

Title
A practical guide to machine learning interatomic potentials -- Status and future Ryan Jacobs D. Morgan Siamak Attarian Jun Meng Chen Shen ... K. J. Schmidt So Takamoto Aidan Thompson Julia Westermayr Brandon M. Wood 59 4 0 12 Mar 2025
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 32 59 0 11 Dec 2022
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 Julia Westermayr P. Marquetand 27 258 0 10 Jul 2020
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning Marcel F. Langer Alex Goessmann M. Rupp AI4CE 25 92 0 26 Mar 2020
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 161 448 0 16 Sep 2019