1 citations · 1 across the 2 of their papers we have counts for
3 papers
DeepAdjoint: An All-in-One Photonic Inverse Design Framework Integrating Data-Driven Machine Learning with Optimization Algorithms
Christopher Yeung, Benjamin Pham, Ryan Tsai +2
In recent years, hybrid design strategies combining machine learning (ML) with electromagnetic optimization algorithms have emerged as a new paradigm for the inverse design of phot…
Hybrid Supervised and Reinforcement Learning for the Design and Optimization of Nanophotonic Structures
Christopher Yeung, Benjamin Pham, Zihan Zhang +2
From higher computational efficiency to enabling the discovery of novel and complex structures, deep learning has emerged as a powerful framework for the design and optimization of…
Global Inverse Design Across Multiple Photonic Structure Classes Using Generative Deep Learning
Christopher Yeung, Ryan Tsai, Benjamin Pham +6
Understanding how nano- or micro-scale structures and material properties can be optimally configured to attain specific functionalities remains a fundamental challenge. Photonic m…