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原子中心神经网络潜力的自动特征选择使用梯度增强决策算法

Renzhe Li1, Jiaqi Wang1, Akksay Singh1,2,3

  • 1Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China.

Journal of chemical theory and computation
|November 19, 2024
PubMed
概括

本研究介绍了一种使用梯度增强决策树 (GBDT) 选择最佳原子中心对称函数 (ACSFs) 准确的原子中心神经网络 (ANN) 潜力的自动化方法. 该方法通过提高准确性和效率来增强机器学习潜力的发展.

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