@inproceedings{2b529582caa34a3fa173380def64db12,
title = "Silicon Photonics for Training Deep Neural Networks",
abstract = "Analog photonic networks as deep learning hardware accelerators are trained on standard digital electronics. We propose an on-chip training of neural networks enabled by a silicon photonic architecture for parallel, efficient, and fast data operations.",
author = "Shastri, \{Bhavin J.\} and Filipovich, \{Matthew J.\} and Zhimu Guo and Prucnal, \{Paul R.\} and Sudip Shekhar and Sorger, \{Volker J.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022 ; Conference date: 31-07-2022 Through 05-08-2022",
year = "2022",
doi = "10.1109/CLEO-PR62338.2022.10432530",
language = "English (US)",
series = "2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022 - Proceedings",
address = "United States",
}