By-passing the Kohn-Sham equations with machine learning

9 September 2016

Papers citing "By-passing the Kohn-Sham equations with machine learning"

8 / 8 papers shown

Title
Predicting fermionic densities using a Projected Quantum Kernel method Francesco Perciavalle Francesco Plastina Michele Pisarra Nicola Lo Gullo 111 0 0 18 Apr 2025
Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory Sergei Manzhos Johann Luder Manabu Ihara Manabu Ihara 56 0 0 08 Feb 2025
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 131 687 0 06 Dec 2017
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals Kevin Vu John C. Snyder Li Li M. Rupp Brandon F. Chen Tarek Khelif K. Müller K. Burke 28 100 0 16 Jan 2015
Understanding Machine-learned Density Functionals Li Li John C. Snyder I. Pelaschier Jessica Huang U. Niranjan Paul Duncan M. Rupp K. Müller K. Burke 40 151 0 04 Apr 2014
Orbital-free Bond Breaking via Machine Learning John C. Snyder M. Rupp K. Hansen Leo Blooston K. Müller K. Burke 51 115 0 07 Jun 2013
Finding Density Functionals with Machine Learning John C. Snyder M. Rupp K. Hansen K. Müller K. Burke 92 476 0 22 Dec 2011
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M. Rupp A. Tkatchenko K. Müller O. A. von Lilienfeld AI4CE 120 1,581 0 12 Sep 2011