Synthetic pre-training for neural-network interatomic potentials
Machine learning (ML) based interatomic potentials have transformed the field of atomistic materials modelling. However, ML potentials depend critically on the quality and quantity of quantum-mechanical reference data with which they are trained, and therefore developing datasets and training pipeli...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
IOP Publishing
2024-01-01
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Series: | Machine Learning: Science and Technology |
Subjects: | |
Online Access: | https://doi.org/10.1088/2632-2153/ad1626 |