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An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.

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mitmath/18337sp2023-minsik_cho-PotentialLearning.jl

 
 

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[WIP] PotentialLearning.jl

An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing. This package is part of a software suite developed for the CESMIX project.

Development documentation MIT license Ask us anything GitHub tag (latest SemVer pre-release)

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An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.

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