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Development of a Python package facilitates accelerated computational processes using neural networks in science.
Development of machine learning tools makes possible to apply them in various fields of science. For example, by creating and training specially designed neural network it is possible to obtain a significant acceleration of computational process compared to ab initio molecular dynamics. This paper presents a Python programming package for creating, training, and applying Behler–Parrinello neural networks using PyTorch framework.
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Budnikov et al. (2026) studied this question.
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