922 citations · 3.5k across the 16 of their papers we have counts for
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Machine Learning for Quantum Mechanical Properties of Atoms in Molecules
Matthias Rupp, Raghunathan Ramakrishnan, O. Anatole von Lilienfeld
We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instant out-of-sample predictions for proton and carbon nuclear chemical shifts, atomi…
Big Data meets Quantum Chemistry Approximations: The -Machine Learning Approach
Raghunathan Ramakrishnan, Pavlo O. Dral, Matthias Rupp +1
Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a com…
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals
Kevin Vu, John Snyder, Li Li +5
Accurate approximations to density functionals have recently been obtained via machine learning (ML). By applying ML to a simple function of one variable without any random samplin…