Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations

Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations

Active learning (AL) requires massive time for comprehensive sampling of complex potential energy surfaces to achieve desirable accuracy and stability of machine learning (ML) potentials. Here, we develop an active delta-learning (ADL) protocol for speeding up AL and building delta-learning models y...

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Bibliographic Details
Main Authors: Yaohuang Huang, Yi-Fan Hou, Pavlo O Dral
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
machine learning interatomic potentials
delta learning
active learning
chemical reactions
molecular dynamics
transition state
Online Access:https://doi.org/10.1088/2632-2153/adeb46
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https://doi.org/10.1088/2632-2153/adeb46

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