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Machine Learning Density Functionals in the Ground-State and for Time-Dependent DFT. (Kieron Burke)
Автор: Francesco Sottile
Загружено: 2022-01-13
Просмотров: 1234
Описание:
I will discuss machine learning in electronic structure theory. I will review recent efforts to use ML to find density functionals for ground-state density functional theory (DFT), both for weakly and strongly correlated systems. I will end with ideas about machine learning in time-dependent (TDDFT).
This talk is part of the Discussion meeting on Machine Learning (http://gdr-rest.polytechnique.fr/Disc..., organised by the GDR REST.
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