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使用改进的机器学习模型进行容错的量子化学计算

Kai Yuan1,2, Shuai Zhou3,4, Ning Li5

  • 1College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China.

Journal of computational chemistry
|July 29, 2024
PubMed
概括

改进的机器学习 (ML) 模型和编码计算提高了分布式科学计算中的负载平衡和容错能力. 这优化了计算资源的使用,用于分子基础和激发状态的自动化量子化学计算.

关键词:
编码计算是编码的计算.激发模式的激发模式一个分散的方法,一个分散的方法.互动的能量是相互作用的能量.负载平衡系统的负载平衡

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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