Training of photonic neural networks through in situ backpropagation. - Tyler W. Hughes; Momchil Minkov; Yu Shi; Shanhui Fan (CoRR, 2018)

Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks. - Ian A. D. Williamson; Tyler W. Hughes; Momchil Minkov; Ben Bartlett; Sunil Pai; Shanhui Fan (CoRR, 2019)

Wave Physics as an Analog Recurrent Neural Network. - Tyler W. Hughes; Ian A. D. Williamson; Momchil Minkov; Shanhui Fan (CoRR, 2019)

Forward-Mode Differentiation of Maxwell's Equations. - Tyler W. Hughes; Ian A. D. Williamson; Momchil Minkov; Shanhui Fan (CoRR, 2019)

Parallel fault-tolerant programming of an arbitrary feedforward photonic network. - Sunil Pai; Ian A. D. Williamson; Tyler W. Hughes; Momchil Minkov; Olav Solgaard; Shanhui Fan; David A. B. Miller (CoRR, 2019)

Inverse design of photonic crystals through automatic differentiation. - Momchil Minkov; Ian A. D. Williamson; Lucio C. Andreani; Dario Gerace; Beicheng Lou; Alex Y. Song; Tyler W. Hughes; Shanhui Fan (CoRR, 2020)

Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks. - Sunil Pai; Zhanghao Sun; Tyler W. Hughes; Taewon Park; Ben Bartlett; Ian A. D. Williamson; Momchil Minkov; Maziyar Milanizadeh; Nathnael Abebe; Francesco Morichetti; Andrea Melloni; Shanhui Fan; et al. (CoRR, 2022)