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Fourier Neural Operator for seismic event localization - ayratabd/FNO_Localization
如何理解Fourier Neural Operator (FNO) - CSDN博客
2024年4月11日 · FNO（Fourier Neural Operator）是一种基于神经网络的方法，主要用于解决偏微分方程（PDEs）。这种方法通过引入傅里叶变换来捕捉全局依赖关系，从而能够高效地处 …
偏微分方程与机器学习: Fourier neural operator (FNO) 详细解读
fno在机器学习求解偏微分方程领域比较火热，是继pinn后一种所谓 "算子学习''的范式，但因为论文中涉及大量数学推导和灵感的阐述让人很难快速理解。
AI与PDE（五）：FNO模型的源代码解析 - 知乎 - 知乎专栏
由于FNO在github上所提供的代码比较简洁，并且功能齐全，很适合通过复现的方式对该模型进行学习和研究，下面直接进入正题去看代码。 2.代码解析 首先先附上源代码的链接， https:// …
