Publikationsrepositorium - Helmholtz-Zentrum Dresden-Rossendorf
1 PublikationDFT Surrogate modeling with the Materials Learning Algorithms (MALA) – Theoretical Background
Abstract
MALA (Materials Learning Algorithms) is a data-driven framework to generate surrogate models of density functional theory calculations based on machine learning. Its purpose is to enable multiscale modeling by bypassing computationally expensive steps in state-of-the-art density functional simulations. In this talk, an overview over the theoretical background that enables estimation of physical quantities based on the local density of states (LDOS) is given.
Keywords: Density Functional Theory; Machine Learning
-
Vortrag (Konferenzbeitrag) (Online Präsentation)
(TD)DFT Student Seminar Series (#5), 03.08.2021, Newark, USA
Downloads
Permalink: https://www.hzdr.de/publications/Publ-33063
Jahre: 2023 2022 2021 2020 2019 2018 2017 2016 2015