49 citations · 104 across the 4 of their papers we have counts for
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An assessment of the structural resolution of various fingerprints commonly used in machine learning
Behnam Parsaeifard, Deb Sankar De, Anders S. Christensen +6
Atomic environment fingerprints are widely used in computational materials science, from machine learning potentials to the quantification of similarities between atomic configurat…
Continuous and Optimally Complete Description of Chemical Environments Using Spherical Bessel Descriptors
Emir Kocer, Jeremy K. Mason, Hakan Erturk
Recently, machine learning potentials have been advanced as candidates to combine the high-accuracy of quantum mechanical simulations with the speed of classical interatomic potent…
A Novel Approach to Describe Chemical Environments in High Dimensional Neural Network Potentials
Emir Kocer, Jeremy K. Mason, Hakan Erturk
A central concern of molecular dynamics simulations are the potential energy surfaces that govern atomic interactions. These hypersurfaces define the potential energy of the system…