Learning to Approximate Density Functionals

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

(2021) Li Li et al.   PHYSICAL REVIEW LETTERS

Neural network interpolation of exchange-correlation functional

(2020) Alexander Ryabov et al.   Scientific Reports

Completing density functional theory by machine learning hidden messages from molecules

(2020) Ryo Nagai et al.   npj Computational Materials

Machine learning accurate exchange and correlation functionals of the electronic density

(2020) Sebastian Dick et al.   Nature Communications

Incompleteness of Atomic Structure Representations

(2020) Sergey N. Pozdnyakov et al.   PHYSICAL REVIEW LETTERS

Quantum chemical accuracy from density functional approximations via machine learning

(2020) Mihail Bogojeski et al.   Nature Communications

An adaptive deep reinforcement learning framework enables curling robots with human-like performance in real-world conditions

(2020) Dong-Ok Won et al.   Science Robotics

Artificial neural networks for density-functional optimizations in fermionic systems

(2019) Caio A. Custódio et al.   Scientific Reports

Deep learning for cellular image analysis

(2019) Erick Moen et al.   NATURE METHODS

Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian Inference

(2019) Ryosuke Jinnouchi et al.   PHYSICAL REVIEW LETTERS

Design and analysis of machine learning exchange-correlation functionals via rotationally invariant convolutional descriptors

(2019) Xiangyun Lei et al.   Physical Review Materials

Machine learning and artificial intelligence to aid climate change research and preparedness

(2019) Chris Huntingford et al.   Environmental Research Letters

Learning from the density to correct total energy and forces in first principle simulations

(2019) Sebastian Dick et al.   JOURNAL OF CHEMICAL PHYSICS

Machine Learning the Physical Nonlocal Exchange–Correlation Functional of Density-Functional Theory

(2019) Jonathan Schmidt et al.   Journal of Physical Chemistry Letters

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

(2019) K. T. Schütt et al.   Nature Communications

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

Semi-local machine-learned kinetic energy density functional with third-order gradients of electron density

(2018) Junji Seino et al.   JOURNAL OF CHEMICAL PHYSICS

Guest Editorial: Special Topic on Data-Enabled Theoretical Chemistry

(2018) Matthias Rupp et al.   JOURNAL OF CHEMICAL PHYSICS

Can exact conditions improve machine-learned density functionals?

(2018) Jacob Hollingsworth et al.   JOURNAL OF CHEMICAL PHYSICS

Nuclear quantum effects enter the mainstream

(2018) Thomas E. Markland et al.   Nature Reviews Chemistry

Deep learning: A guide for practitioners in the physical sciences

(2018) Brian K. Spears et al.   PHYSICS OF PLASMAS

A look at the density functional theory zoo with the advanced GMTKN55 database for general main group thermochemistry, kinetics and noncovalent interactions

(2017) Lars Goerigk et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Bypassing the Kohn-Sham equations with machine learning

(2017) Felix Brockherde et al.   Nature Communications

Optimization of an exchange-correlation density functional for water

(2016) Michelle Fritz et al.   JOURNAL OF CHEMICAL PHYSICS

Kinetic Energy of Hydrocarbons as a Function of Electron Density and Convolutional Neural Networks

(2016) Kun Yao et al.   Journal of Chemical Theory and Computation

Nonlinear gradient denoising: Finding accurate extrema from inaccurate functional derivatives

(2015) John C. Snyder et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Understanding machine-learned density functionals

(2015) Li Li et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Understanding kernel ridge regression: Common behaviors from simple functions to density functionals

(2015) Kevin Vu et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Strongly Constrained and Appropriately Normed Semilocal Density Functional

(2015) Jianwei Sun et al.   PHYSICAL REVIEW LETTERS

The density matrix renormalization group for ab initio quantum chemistry

(2014) Sebastian Wouters et al.   EUROPEAN PHYSICAL JOURNAL D

Ions in solution: Density corrected density functional theory (DC-DFT)

(2014) Min-Cheol Kim et al.   JOURNAL OF CHEMICAL PHYSICS

Orbital-free bond breaking via machine learning

(2013) John C. Snyder et al.   JOURNAL OF CHEMICAL PHYSICS

DFT in a nutshell

(2012) Kieron Burke et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Perspective on density functional theory

(2012) Kieron Burke   JOURNAL OF CHEMICAL PHYSICS

One-Dimensional Continuum Electronic Structure with the Density-Matrix Renormalization Group and Its Implications for Density-Functional Theory

(2012) E. M. Stoudenmire et al.   PHYSICAL REVIEW LETTERS

Finding Density Functionals with Machine Learning

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

Insights into Current Limitations of Density Functional Theory

(2008) A. J. Cohen et al.   SCIENCE