AutoML Hyperparameter Tuning of Generative DNN Architecture for Nanophotonic Device Design

We introduce an automated machine learning (AutoML) framework to construct a deep neural network model relevant for inverse design of nanophotonic devices without relying on manual trial-and-error hyperparameter tuning.