ConceptBehler-Parrinello对称函数
Behler-Parrinello
A representative method in the field of machine learning potentials that constructs high-dimensional neural network potential energy surfaces by describing the local environment of atoms through symmetry functions.
Timeline (last 90 days)
Oct 18
Machine learning potentials (MLP) are methods that use first-principles calculation data as training labels and fit interatomic potential energy surfaces and forces with machine learning models, with representative work including Behler-Parrinello symmetry functions, Gaussian approximation potentials (GAP) and neural network potentials (such as ANI and MACE).
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