The code for the paper Florido, J., Wang, H., Khan, A., Jimack, P.K. (2024). Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs. In: Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2024. ICCS 2024. Lecture Notes in Computer Science, vol 14834. Springer, Cham. https://doi.org/10.1007/978-3-031-63759-9_36, looking at using different sources of guiding information to guide adaptive sampling as described in 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.
To cite this code for your own academic research please cite the paper:
@InProceedings{10.1007/978-3-031-63759-9_36,
author="Florido, Jose and Wang, He and Khan, Amirul and Jimack, Peter K.",
editor="Franco, Leonardo and de Mulatier, Cl{\'e}lia and Paszynski, Maciej and Krzhizhanovskaya, Valeria V. and Dongarra, Jack J. and Sloot, Peter M. A.",
title="Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs",
booktitle="Computational Science -- ICCS 2024",
year="2024",
publisher="Springer Nature Switzerland",
address="Cham",
pages="323--337",
}