The data and code for the paper C. Wu, M. Zhu, Q. Tan, Y. Kartha, & L. Lu. A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks. Computer Methods in Applied Mechanics and Engineering, 403, 115671, 2023.
- Diffusion equation
- Burgers’ equation
- Allen–Cahn equation
- Wave equation
- Diffusion–reaction equation (inverse problem)
- Korteweg–de Vries equation (inverse problem)
If you use this data or code for academic research, you are encouraged to cite the following paper:
@article{wu2023comprehensive,
title = {A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks},
author = {Wu, Chenxi and Zhu, Min and Tan, Qinyang and Kartha, Yadhu and Lu, Lu},
journal = {Computer Methods in Applied Mechanics and Engineering},
volume = {403},
pages = {115671},
year = {2023},
doi = {https://doi.org/10.1016/j.cma.2022.115671}
}
To get help on how to use the data or code, simply open an issue in the GitHub "Issues" section.