Data for: GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems
https://doi.org/10.71870/8e3q-j519
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.orgOpens in a new tab). The complete descriptions of all variables contained in the data are found in the article.
Citation and access
Citation and access
Data access level:
Creator/Principal investigator(s):
- Simon Stenmark - Chalmers University of Technology
Research principal:
Data contains personal data:
No
Citation:
Language:
Method and outcome
Method and outcome
Data format/data structure:
Data collection - Simulation
Data collection - Simulation
Mode of collection:
Simulation
Description of the mode of collection:
The data was created using the finite element method as described in the article.
Administrative information
Administrative information
Responsible department/unit:
Department of Electrical Engineering
Topic and keywords
Topic and keywords
Standard för svensk indelning av forskningsämnen 2025:
Publications
Publications
Citation:
S. Stenmark, T. Rylander, T. McKelvey, and A. Ludvig-Osipov, “GIANT Networks: Very Deep Fully Connected Neural Networks Applied to Microwave Problems,” IET Microwaves, Antennas & Propagation
Metadata
Metadata
Version 1
