Fourier Neural Operator 模型是Fourier Neural Operator for Parametric Partial Differential Equations一文中提出的模型。该模型尝试去学习基于傅里叶变换的有限维算子的参数化,去数值逼近一些偏微分方程。该模型比起其他尝试用深度学习求解复杂的偏微分方程数值解的模型相比,具备以下几个很重要的特点: 训练比较容易,可以用...
For partial differential equations (PDEs), neural operators directly learn the mapping from any functional parametric dependence to the solution. Thus, they learn an entire family of PDEs, in contrast to classical methods which solve one instance of the equation. In this work, we formulate a new...
Fourier Neural Operator for Parametric Partial Differential EquationsZongyi LiNikola Borislavov KovachkiKamyar AzizzadenesheliBurigede liuKaushik BhattacharyaAndrew StuartAnima AnandkumarInternational Conference on Learning Representations
Fourier Neural Operator for Parametric Partial Differential Equations. In International Conference on Learning Representations (ICLR), 2021a. (https://openreview.net/forum?id=c8P9NQVtmnO)Example: Fourier Neural Operator for 1d Burgers' Equation
A boundary-based fourier neural operator (B-FNO) method for efficient parametric acoustic wave analysis doi:10.1007/s00366-024-02103-xRepetitive wave analysis is required in various applications involving parametric analyses across different settings. However, traditional numerical methods based on domain ...
Li, Z. Y. et al. Fourier neural operator for parametric partial differential equations. The 9thInternational Conference on Learning Representations (ICLR-21).https://iclr.cc/virtual/2021/poster/3281(2021). Bishara, W. et al. Lensfree on-chip microscopy over a wide field-of-view using pixel...
fourier_neural_operator-master.zip FOURIER NEURAL OPERATOR FOR PARAMETRIC PARTIAL DIFFERENTIAL EQUATIONS论文源码 上传者:qq_37245700时间:2021-10-21 算法参考资料Fourier-transform-叉姐(交大郭晓旭) 算法参考资料Fourier_transform-叉姐(交大郭晓旭)提取方式是百度网盘分享地址 ...
Now we show how the quantum Fourier transform defined in the last subsection can be used in an algorithm for phase estimation. This quantum algorithm solves the following problem: • Phase Estimation:A unitary operator U has an eigenvector |u〉 with eigenvalue e2 πiφ, where the value of...
Laplace neural operator for solving differential equations Article24 June 2024 Machine-learning-based spectral methods for partial differential equations ArticleOpen access31 January 2023 Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators ...
Krim, H., Viberg, M.: Two decades of array signal processing research: the parametric approach. IEEE Signal Process. Mag. 13(4), 67–94 (1996) Article Google Scholar Kurková, V., Sanguineti, M.: Bounds on rates of variable basis and neural network approximation. IEEE Trans. Inf. The...