Nonlinear gradient denoising: Finding accurate extrema from inaccurate functional derivatives

DFT: A Theory Full of Holes?

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

Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment

(2013) Gregoire Montavon et al.   IEEE SIGNAL PROCESSING MAGAZINE

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

Machine learning of molecular electronic properties in chemical compound space

(2013) Grégoire Montavon et al.   NEW JOURNAL OF PHYSICS

Issues and challenges in orbital-free density functional calculations

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

Optimizing transition states via kernel-based machine learning

(2012) Zachary D. Pozun et al.   JOURNAL OF CHEMICAL PHYSICS

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

The NumPy Array: A Structure for Efficient Numerical Computation

(2011) Stéfan van der Walt et al.   COMPUTING IN SCIENCE & ENGINEERING

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

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