All credit for the code goes to the authors of the original repository https://github.com/ConstitutiveANN/CANN. This repository is a fork of the original, with modifications made by Héctor Lobato, researcher at Leartiker.

Article: K. Linka, M. Hillgärtner, K. P. Abdolazizi, R. C. Aydin, M. Itskov, & C. J. Cyron (2021). Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning. Journal of Computational Physics, 429, 110010. https://doi.org/10.1016/j.jcp.2020.110010

The CANN architecture was developed and tested in the following environment:

Python: 3.8.3; keras: 2.4.2; tensorflow: 2.2.0; pandas: 1.0.5; numpy: 1.19.0; matplotlib: 3.2.2

You can run "versions.py" to display the versions currently used on your system.