Data for: GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems
Abstract
This dataset contains the samples of the training, validation and test data sets for the two numerical examples of the article ''GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems'' (Stenmark, Rylander, McKelvey & Ludvig-Osipov, 2026). All data is created using the finite element method as described in the article and is stored in the NPZ format which can be opened with the Python library NumPy (https://numpy.org/). The complete descriptions of all variables contained in the data are found in the article.
Fields of Study & Subjects
Model Reduction and Neural Networks
Electromagnetic Simulation and Numerical Methods
Neural Networks and Applications
Publication details
- Journal / source
- Chalmers University of Technology / DORIS repository
- Publication date
- 10 February 2026
- Language
- EN
- Document type
- Dataset