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19922026
most citedFast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

2.4k citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing 2013 · physics.chem-phShow all

5 papers · 2 filters

physics.chem-ph2013★ 15 cited

Topology of surfaces for molecular Stark energy, alignment and orientation generated by combined permanent and induced electric dipole interactions

Burkhard Schmidt, Bretislav Friedrich

We show that combined permanent and induced electric dipole interactions of polar and polarizable molecules with collinear electric fields lead to a sui generis topology of the cor…

physics.chem-ph2013★ 658 cited

Long-range correlation energy calculated from coupled atomic response functions

Alberto Ambrosetti, Anthony M. Reilly, Robert A. DiStasio +1

An accurate determination of the electron correlation energy is essential for describing the structure, stability, and function in a wide variety of systems, ranging from gas-phase…

physics.chem-ph2013★ 140 cited

Orbital-free Bond Breaking via Machine Learning

John C. Snyder, Matthias Rupp, Katja Hansen +3

Machine learning is used to approximate the kinetic energy of one dimensional diatomics as a functional of the electron density. The functional can accurately dissociate a diatomic…

physics.chem-ph2013★ 635 cited

Machine Learning of Molecular Electronic Properties in Chemical Compound Space

Grégoire Montavon, Matthias Rupp, Vivekanand Gobre +5

The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identifica…

physics.chem-ph2013

Stark deceleration of NO radicals

Xingan Wang, Moritz Kirste, Gerard Meijer +1

We report on the Stark deceleration of a pulsed molecular beam of NO radicals. Stark deceleration of this chemically important species has long been considered unfeasible due to it…