Learning-based physics-enhanced modeling and inline material characterization for electromagnetics
This thesis explores possibilities for combining physics-based and learning-based techniques to create efficient hybrid methods for electromagnetic problems and proposes and evaluates Gradient-Informed Attentive Normalization Training (GIANT), a neural network training procedure for constructing computationally efficie...