Poster
in
Workshop: AI for Science: Mind the Gaps
Generative Neural Network Based Non-Convex Optimization Using Policy Gradients with an Application to Electromagnetic Design
Sean Hooten
Abstract:
A generative neural network based non-convex optimization algorithm using a one-step implementation of the policy gradient method is introduced and applied to electromagnetic design. We demonstrate state-of-the-art performance of electromagnetic devices called grating couplers, with key advantages over local gradient-based optimization via the adjoint method.