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Machine learning and density functional theory

Over the past decade machine learning has made significant advances in approximating density functionals, but whether this signals the end of human-designed functionals remains to be seen. Ryan Pederson, Bhupalee Kalita and Kieron Burke discuss the rise of machine learning for functional design.

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Work supported by DOE DE-SC0008696 (R.P.) and NSF CHE-2154371 (B.K., K.B.).

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Correspondence to Kieron Burke.

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Pederson, R., Kalita, B. & Burke, K. Machine learning and density functional theory. Nat Rev Phys 4, 357–358 (2022).

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