Highly accurate machine learning model for kinetic energy density functional

Kohn-Sham Equations as Regularizer: Building Prior Knowledge into Machine-Learned Physics

(2021) Li Li et al.   PHYSICAL REVIEW LETTERS

CONUNDrum: A program for orbital-free density functional theory calculations

(2020) Pavlo Golub et al.   COMPUTER PHYSICS COMMUNICATIONS

Completing density functional theory by machine learning hidden messages from molecules

(2020) Ryo Nagai et al.   npj Computational Materials

Machine Learning Approaches Toward Orbital-free Density Functional Theory: Simultaneous Training on the Kinetic Energy Density Functional and its Functional Derivative

(2020) Ralf Meyer et al.   Journal of Chemical Theory and Computation

A high-bias, low-variance introduction to Machine Learning for physicists

(2019) Pankaj Mehta et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

Using Pauli energy to appraise the quality of approximate semilocal non-interacting kinetic energy density functionals

(2019) Siyuan Liu et al.   JOURNAL OF CHEMICAL PHYSICS

A local environment descriptor for machine-learned density functional theory at the generalized gradient approximation level

(2018) Hyunjun Ji et al.   JOURNAL OF CHEMICAL PHYSICS

Experimental Machine Learning of Quantum States

(2018) Jun Gao et al.   PHYSICAL REVIEW LETTERS

Kinetic energy density for orbital-free density functional calculations by axiomatic approach

(2017) Fahhad H. Alharbi et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Bypassing the Kohn-Sham equations with machine learning

(2017) Felix Brockherde et al.   Nature Communications

One-dimensional mimicking of electronic structure: The case for exponentials

(2015) Thomas E. Baker et al.   PHYSICAL REVIEW B

Density functional theory: Its origins, rise to prominence, and future

(2015) R. O. Jones   REVIEWS OF MODERN PHYSICS

The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

(2015) Scott Kirklin et al.   npj Computational Materials

Modelling self trapping and trap mutation in tungsten using DFT and Molecular Dynamics with an empirical potential based on DFT

(2014) J. Boisse et al.   JOURNAL OF NUCLEAR MATERIALS

Density functional theory: Foundations reviewed

(2014) Eugene S. Kryachko et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

Efficient construction of exchange and correlation potentials by inverting the Kohn–Sham equations

(2013) Alexei A. Kananenka et al.   JOURNAL OF CHEMICAL PHYSICS

Laplacian-Level Kinetic Energy Approximations Based on the Fourth-Order Gradient Expansion: Global Assessment and Application to the Subsystem Formulation of Density Functional Theory

(2013) Savio Laricchia et al.   Journal of Chemical Theory and Computation

Issues and challenges in orbital-free density functional calculations

(2012) V.V. Karasiev et al.   COMPUTER PHYSICS COMMUNICATIONS

Can orbital-free density functional theory simulate molecules?

(2012) Junchao Xia et al.   JOURNAL OF CHEMICAL PHYSICS

Finding Density Functionals with Machine Learning

(2012) John C. Snyder et al.   PHYSICAL REVIEW LETTERS