不确定性驱动的动力学,用于积极学习原子间潜能

Maksim Kulichenko1, Kipton Barros2,3, Nicholas Lubbers4

  • 1Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA. maxim@lanl.gov.

PubMed
概括

本研究介绍了主动学习的不确定性驱动动力学 (UDD-AL),这是一种新的方法,可以加速发现用于训练机器学习模型的关键数据. UDD-AL有效地探索复杂的化学空间,以进行更准确的模拟.

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