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DeepONet & FNO (with practical extensions)

License: Other

Python 92.11% MATLAB 7.89%

deeponet-fno's Introduction

DeepONet & FNO (with practical extensions)

The data and code for the paper L. Lu, X. Meng, S. Cai, Z. Mao, S. Goswami, Z. Zhang, & G. E. Karniadakis. A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data. Computer Methods in Applied Mechanics and Engineering, 393, 114778, 2022.

Datasets

Code

Cite this work

If you use this data or code for academic research, you are encouraged to cite the following paper:

@article{lu2022comprehensive,
  title   = {A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data},
  author  = {Lu, Lu and Meng, Xuhui and Cai, Shengze and Mao, Zhiping and Goswami, Somdatta and Zhang, Zhongqiang and Karniadakis, George Em},
  journal = {Computer Methods in Applied Mechanics and Engineering},
  volume  = {393},
  pages   = {114778},
  year    = {2022}
}

Questions

To get help on how to use the data or code, simply open an issue in the GitHub "Issues" section.

License

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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