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

DFT: A Theory Full of Holes?

(2015) Aurora Pribram-Jones et al.   Annual Review of Physical Chemistry

Nonlinear gradient denoising: Finding accurate extrema from inaccurate functional derivatives

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

How to represent crystal structures for machine learning: Towards fast prediction of electronic properties

(2014) K. T. Schütt et al.   PHYSICAL REVIEW B

Orbital-free bond breaking via machine learning

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

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies

(2013) Katja Hansen et al.   Journal of Chemical Theory and Computation

Finding Density Functionals with Machine Learning

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

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

Electronic Structure via Potential Functional Approximations

(2011) Attila Cangi et al.   PHYSICAL REVIEW LETTERS

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS

Dynamics of learning near singularities in radial basis function networks

(2008) Haikun Wei et al.   NEURAL NETWORKS