41 citations · 59 across the 5 of their papers we have counts for
5 papers
Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization
Yuheng Chen, Alexander Montes McNeil, Taehyuk Park +16
Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applicatio…
PearSAN: A Machine Learning Method for Inverse Design using Pearson Correlated Surrogate Annealing
Michael Bezick, Blake A. Wilson, Vaishnavi Iyer +6
PearSAN is a machine learning-assisted optimization algorithm applicable to inverse design problems with large design spaces, where traditional optimizers struggle. The algorithm l…
Non-native Quantum Generative Optimization with Adversarial Autoencoders
Blake A. Wilson, Jonathan Wurtz, Vahagn Mkhitaryan +5
Large-scale optimization problems are prevalent in several fields, including engineering, finance, and logistics. However, most optimization problems cannot be efficiently encoded…
A Relative Church-Turing-Deutsch Thesis from Special Relativity and Undecidability
Blake Wilson, Ethan Dickey, Vaishnavi Iyer +1
Beginning with Turing's seminal work in 1950, artificial intelligence proposes that consciousness can be simulated by a Turing machine. This implies a potential theory of everythin…
Machine Learning Framework for Quantum Sampling of Highly-Constrained, Continuous Optimization Problems
Blake A. Wilson, Zhaxylyk A. Kudyshev, Alexander V. Kildishev +3
In recent years, there is a growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-base…