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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Acknowledgements
Work supported by DOE DE-SC0008696 (R.P.) and NSF CHE-2154371 (B.K., K.B.).
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Pederson, R., Kalita, B. & Burke, K. Machine learning and density functional theory. Nat Rev Phys 4, 357–358 (2022). https://doi.org/10.1038/s42254-022-00470-2
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DOI: https://doi.org/10.1038/s42254-022-00470-2
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