2 code implementations • 19 May 2022 • Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs
Finding accurate solutions to the Schr\"odinger equation is the key unsolved challenge of computational chemistry.
5 code implementations • 18 May 2021 • Michael Scherbela, Rafael Reisenhofer, Leon Gerard, Philipp Marquetand, Philipp Grohs
Accurate numerical solutions for the Schr\"odinger equation are of utmost importance in quantum chemistry.
no code implementations • 15 Jul 2020 • Julia Westermayr, Philipp Marquetand
ii) We investigate the transferability of our excited-state ML models in chemical space, i. e., whether an ML model can predict properties of molecules that it has never been trained on and whether it can learn the different excited states of two molecules simultaneously.
no code implementations • 10 Jul 2020 • Julia Westermayr, Philipp Marquetand
Discussed applications of machine learning for excited states include excited-state dynamics simulations, static calculations of absorption spectra, as well as many others.
no code implementations • 28 May 2020 • Julia Westermayr, Philipp Marquetand
Machine learning is employed at an increasing rate in the research field of quantum chemistry.
1 code implementation • 17 Feb 2020 • Julia Westermayr, Michael Gastegger, Philipp Marquetand
The properties are multiple energies, forces, nonadiabatic couplings and spin-orbit couplings.
no code implementations • 18 Dec 2019 • Julia Westermayr, Felix A. Faber, Anders S. Christensen, O. Anatole von Lilienfeld, Philipp Marquetand
As an ultimate test for our machine learning models, we carry out excited-state dynamics simulations based on the predicted energies, forces and couplings and, thus, show the scopes and possibilities of machine learning for the treatment of electronically excited states.
no code implementations • 18 Dec 2018 • Michael Gastegger, Philipp Marquetand
Molecular dynamics simulations are an important tool for describing the evolution of a chemical system with time.
no code implementations • 22 Nov 2018 • Julia Westermayr, Michael Gastegger, Maximilian F. S. J. Menger, Sebastian Mai, Leticia González, Philipp Marquetand
Photo-induced processes are fundamental in nature, but accurate simulations are seriously limited by the cost of the underlying quantum chemical calculations, hampering their application for long time scales.
no code implementations • 15 Dec 2017 • Michael Gastegger, Ludwig Schwiedrzik, Marius Bittermann, Florian Berzsenyi, Philipp Marquetand
We introduce weighted atom-centered symmetry functions (wACSFs) as descriptors of a chemical system's geometry for use in the prediction of chemical properties such as enthalpies or potential energies via machine learning.
no code implementations • 16 May 2017 • Michael Gastegger, Jörg Behler, Philipp Marquetand
Machine learning has emerged as an invaluable tool in many research areas.