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Updated: Mar 11, 2026

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在神经PDE解答器和操作者学习中基于残余的适应性的一个变化框架.

Juan Diego Toscano1, Daniel T Chen1, Vivek Ooomen2

  • 1Division of Applied Mathematics, Brown University, Providence, RI USA.

NPJ artificial intelligence
|March 10, 2026
PubMed
概括

我们在科学机器学习中引入了基于残余的适应性策略的变化框架. 这种方法使启发式方法正式化,使系统设计成为可能,并减少对增强学习动态的分类错误.

关键词:
工程 工程师 工程师 工程师数学和计算的数学和计算.

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