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Updated: Sep 18, 2025

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探索量子化学机器学习模型的设计空间,使用完全可差异化的框架.

Divya Suman1, Jigyasa Nigam1, Sandra Saade1

  • 1Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.

Journal of chemical theory and computation
|June 25, 2025
PubMed
概括

本研究引入了混合机器学习 (ML) 和量子力学 (QM) 模型的新框架. 它可以通过预测电子哈密尔顿数来对QM属性进行间接训练,从而改善模型设计和准确性.

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