TY - DATA
T1 - Code supporting the paper: DeepONet models for predicting post-burn contraction
PY - 2024/10/30
AU - Selma Husanović
AU - Alexander Heinlein
AU - Ginger Egberts
AU - Fred Vermolen
UR - 
DO - 10.4121/69d1aefc-a01d-4280-8b32-5c8420d9a2a3.v1
KW - Operator learning
KW - DeepONet
KW - Surrogate model
KW - Post-burn contraction
N2 - <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>
ER -