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Kohn-Sham density functional theory is the base of modern computational approaches to electronic structures.
A simplification of the hartree-fock method
Slater, J. C · 1951
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Inhomogeneous electron gas
Hohenberg, P. & Kohn, W · 1964
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Self-consistent equations including exchange and correlation effects
Kohn, W. & Sham, L. J · 1965
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Descriptions of exchange and correlation effects in inhomogeneous electron systems
Gunnarsson, O., Jonson, M. & Lundqvist, B. I · 1979
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Spin-density gradient expansion for the kinetic energy
Oliver, G. L. & Perdew, J. P · 1979
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Accurate spin-dependent electron liquid correlation energies for local spin density calculations: a critical analysis
Vosko, S. H., Wilk, L. & Nusair, M · 1980
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A full coupled-cluster singles and doubles model: The inclusion of disconnected triples
Purvis, G. D. & Bartlett, R. J · 1982
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Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E. & Williams, R. J · 1986
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Density-functional exchange-energy approximation with correct asymptotic behavior
Becke, A. D · 1988
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Development of the colle-salvetti correlation-energy formula into a functional of the electron density
Lee, C., Yang, W. & Parr, R. G · 1988
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Approximation capabilities of multilayer feedforward networks
Hornik, K · 1991
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Ab initio calculation of vibrational absorption and circular dichroism spectra using density functional force fields
Stephens, P. J., Devlin, F. J., Chabalowski, C. F. & Frisch, M. J · 1994
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Generalized gradient approximation made simple
Perdew, J. P., Burke, K. & Ernzerhof, M · 1996
Cited alongside, same era.
Exchange-correlation potentials
Tozer, D. J., Ingamells, V. E. & Handy, N. C · 1996
Cited alongside, same era.
Assessment of gaussian-2 and density functional theories for the computation of enthalpies of formation
Curtiss, L. A., Raghavachari, K., Redfern, P. C. & Pople, J. A · 1997
Cited alongside, same era.
Assessment of the perdew-burke-ernzerhof exchange-correlation functional
Ernzerhof, M. & Scuseria, G. E · 1999
Cited alongside, same era.
Many-Particle Physics (Physics of Solids and Liquids) (Springer, Berlin, 2000)
Mahan, G. D · 2000
Cited alongside, same era.
Jacob’s ladder of density functional approximations for the exchange-correlation energy
Perdew, J. P. & Schmidt, K · 2001
Strongly constrained and appropriately normed semilocal density functional
Sun, J., Ruzsinszky, A. & Perdew, J. P · 2015
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Fast and accurate deep network learning by exponential linear units (elus)
Clevert, D.-A., Unterthiner, T. & Hochreiter, S · 2015
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Density functional theory is straying from the path toward the exact functional
Medvedev, M. G., Bushmarinov, I. S., Sun, J., Perdew, J. P. & Lyssenko, K. A · 2017
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Bypassing the kohn-sham equations with machine learning
Brockherde, F. et al · 2017
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Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals
Mardirossian, N. & Head-Gordon, M · 2017
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Pyscf: the python-based simulations of chemistry framework
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Cited alongside, same era.
Climbing the density functional ladder: Nonempirical meta–generalized gradient approximation designed for molecules and solids
Tao, J., Perdew, J. P., Staroverov, V. N. & Scuseria, G. E · 2003
Cited alongside, same era.
Benchmark database of barrier heights for heavy atom transfer, nucleophilic substitution, association, and unimolecular reactions and its use to test theoretical methods
Zhao, Y., González-García, N. & Truhlar, D. G · 2005
Cited alongside, same era.
Prescription for the design and selection of density functional approximations: More constraint satisfaction with fewer fits
Perdew, J. P. et al · 2005
Cited alongside, same era.
A new local density functional for main-group thermochemistry, transition metal bonding, thermochemical kinetics, and noncovalent interactions
Zhao, Y. & Truhlar, D. G · 2006
Cited alongside, same era.
The m06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four m06-class functionals and 12 other functionals
Zhao, Y. & Truhlar, D. G · 2008
Cited alongside, same era.
Finding density functionals with machine learning
Snyder, J. C., Rupp, M., Hansen, K., Müller, K.-R. & Burke, K · 2012
Cited alongside, same era.
Sun, Q. et al · 2017
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Automatic differentiation in pytorch
Paszke, A. et al · 2017
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Neural-network kohn-sham exchange-correlation potential and its out-of-training transferability
Nagai, R., Akashi, R., Sasaki, S. & Tsuneyuki, S · 2018
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Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties
Xie, T. & Grossman, J. C · 2018
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Can exact conditions improve machine-learned density functionals?
Hollingsworth, J., Li, L. 李., Baker, T. E. & Burke, K · 2018
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Machine learning the physical non-local exchange-correlation functional of density-functional theory
Schmidt, J., Benavides-Riveros, C. L. & Marques, M. A. L · 2019
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Solving the electronic structure problem with machine learning
Chandrasekaran, A. et al · 2019
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