112 citations · 633 across the 32 of their papers we have counts for
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physics.chem-ph2021★ 35 cited
Machine learning the derivative discontinuity of density-functional theory
Johannes Gedeon, Jonathan Schmidt, Matthew J. P. Hodgson +3
Machine learning is a powerful tool to design accurate, highly non-local, exchange-correlation functionals for density functional theory. So far, most of those machine learned func…
quant-ph2021★ 24 cited
Machine Learning Universal Bosonic Functionals
Jonathan Schmidt, Matteo Fadel, Carlos L. Benavides-Riveros
The one-body reduced density matrix plays a fundamental role in describing and predicting quantum features of bosonic systems, such as Bose-Einstein condensation. The recently…