%0 Generic
%A Husanović, Selma
%A Heinlein, Alexander
%A Egberts, Ginger
%A Vermolen, Fred
%D 2024
%T Code supporting the paper: DeepONet models for predicting post-burn contraction
%U 
%R 10.4121/69d1aefc-a01d-4280-8b32-5c8420d9a2a3.v1
%K Operator learning
%K DeepONet
%K Surrogate model
%K Post-burn contraction
%X <p>This online resource provides the relevant data for the forthcoming article <em>DeepONet models for predicting post-burn contraction. </em>The archived folder "data.zip" contains MATLAB data files for training and evaluating the DeepONet models. These datasets were created using MATLAB code available at <a href="https://doi.org/10.4121/21257199" target="_blank">https://doi.org/10.4121/21257199</a>. The Python code for handling the MATLAB data, training, and evaluating the DeepONet models is available at <a href="https://github.com/Selma24/DeepONet-contraction" target="_blank">https://github.com/Selma24/DeepONet-contraction</a>.</p>
%I 4TU.ResearchData