Repository for the paper "Neural Networks for the approximation of Euler's elastica". The preprint of the paper can be found at: https://arxiv.org/abs/2312.00644.
The codebase depends on the dependencies collected in the files "requirements.txt" found in each main folder. To install the necessary packages for each network, run the respective scripts
pip install -r requirements.txt
The codes are organized into 3 main folders:
- ContinuousNetwork, collecting experiments from Section 5.1 of the manuscript,
- ContinuousNetworkTheta, collecting experiments from Section 5.2 of the manuscript,
- DiscreteNetwork, collecting experiments from Section 4.1 of the manuscript.
We add to each of these subdirectories a short readme file to facilitate running the code.
The folder DataSets contains the beam code used to generate the data sets, and the two data sets (both-ends and right-end) mentioned in the paper.
Citation key: @article{celledoni2023neural, title={Neural networks for the approximation of Euler's elastica}, author={Elena Celledoni and Ergys Çokaj and Andrea Leone and Sigrid Leyendecker and Davide Murari and Brynjulf Owren and Rodrigo T. Sato Martín de Almagro and Martina Stavole}, journal={arXiv preprint arXiv:2312.00644}, year={2023} }