Bayesian Learning for Uncertainty Quantification, Optimization, and Inverse Design

Design of microwave circuits require extensive simulations, which often take significant computational time due to design complexity. This can be addressed through neural networks (NNs) that provide predictive capability. Predictions often come with uncertainties that need to be quantified. Moreover...

Ausführliche Beschreibung