比较水的机器学习潜力:基于内核的回归和Behler-Parrinello神经网络

Pablo Montero de Hijes1,2, Christoph Dellago1, Ryosuke Jinnouchi3

  • 1University of Vienna, Faculty of Physics, Kolingasse 14, A-1090 Vienna, Austria.

PubMed
概括

机器学习潜力 (MLP) 可以准确预测水的热力学特性. 对于可靠的模拟,高质量的数据比特定的装配方法更为重要.

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