Numerical and experimental generated data during project https://doi.org/10.1038/s41598-023-45890-x

The dataset was generated using a procedure for low-cost modeling of microwave components utilizing random observables. The major contributions of the work include the implementation of the explicit dimensionality reduction of the confined surrogate model domain and the introduction of this concept into a complete cost-efficient framework for the modeling of microwave components. Comprehensive benchmarking demonstrates excellent performance of the introduced framework, both in terms of the predictive power of the rendered surrogates, their scalability properties, as well as low computational overhead associated with the model setup.