Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method
- Author(s)
- Lukas Exl, Norbert J. Mauser, Sebastian Schaffer, Thomas Schrefl, Dieter Suess
- Organisation(s)
- Department of Mathematics, Research Platform MMM Mathematics-Magnetism-Materials, Faculty of Physics, Physics of Functional Materials
- External organisation(s)
- Wolfgang Pauli Institute (WPI) Vienna, University for Continuing Education Krems
- Journal
- Journal of Computational Physics
- Volume
- 444
- No. of pages
- 20
- ISSN
- 0021-9991
- DOI
- https://doi.org/10.1016/j.jcp.2021.110586
- Publication date
- 11-2021
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 101014 Numerical mathematics, 103043 Computational physics, 102019 Machine learning
- Keywords
- ASJC Scopus subject areas
- Computational Mathematics, Physics and Astronomy(all), Applied Mathematics, Numerical Analysis, Computer Science Applications, Modelling and Simulation, Physics and Astronomy (miscellaneous)
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/prediction-of-magnetization-dynamics-in-a-reduced-dimensional-feature-space-setting-utilizing-a-lowrank-kernel-method(f946783f-b88a-48e5-a6a5-58416d731cee).html