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arXiv Machine Learning By Can Polat, Mustafa Kurban, Erchin Serpedin, Hasan Kurban

When do machine-learned exchange-correlation improvements inherit into density-functional tight binding?

Read the original on arXiv Machine Learning →

arXiv:2608. 14875v1 Announce Type: cross Abstract: Machine-learned exchange-correlation functionals correct band gaps at near-semilocal cost, while density-functional tight binding reaches the $10^3$-$10^6$-atom regime; combining them assumes that a better parent yields a better parameterization, but we show it does not.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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