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Updated: Jun 16, 2026

Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method
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Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method

Published on: July 19, 2019

在PES-Learn中的方法:波恩-奥本海默潜在能量表面的直接适合机器学习

Ian T Beck1, Justin M Turney1, Henry F Schaefer1

  • 1Department of Chemistry, Center for Computational Quantum Chemistry, University of Georgia, Athens, GA 30602, USA.

Molecules (Basel, Switzerland)
|January 10, 2026
PubMed
概括

PES-Learn 1.0是一个新的开源软件,用于构建分子潜在能量表面 (PES) 的机器学习模型. 它引入了内核回归和增强的Python API,以更轻松地构建PES和梯度预测.

关键词:
核心脊回归的回归方法机器学习是机器学习.神经网络的神经网络的神经网络潜在的表面能量 表面能量

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