Physics-informed machine learning: a hybrid lens for fluid dynamics
摘要
Nature Machine Intelligence 在线发表的一项研究提出一种神经网络方法，衔接拉格朗日与欧拉两种视角，将稀疏观测转换为复杂且混沌流体运动的高分辨率物理准确图谱。论文由 Kai Fukami 撰写，DOI 为 10.1038/s42256-026-01319-4。
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正文 · 原文
Nature Machine Intelligence, Published online: 20 October 2026; doi:10.1038/s42256-026-01319-4
A neural network approach bridging Lagrangian and Eulerian perspectives transforms sparse observations into physically accurate, high-resolution maps of complex and chaotic fluid motions.
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来源：Nature Machine Intelligence · nature.com
引用原文
Kai Fukami. Physics-informed machine learning: a hybrid lens for fluid dynamics[EB/OL]. (2026-10-20)[访问日期]. https://www.nature.com/articles/s42256-026-01319-4.