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Keyword: neural network representations ×Clear all

1 claim from 1 paper

1. Materials Science › Machine Learning in Materials Science

   Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

   Behler and Parrinello · Physical Review Letters · 2007

   The paper introduces a neural-network representation of DFT potential-energy surfaces that is much faster than DFT, and tests its accuracy on bulk silicon against empirical potentials and DFT.

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   1. UncheckedThe authors state that their neural-network method for modelling atomic energies is general and applies to all periodic and non-periodic systems.“The method is general and can be applied to all types of periodic and nonperiodic systems.”