@inproceedings{219ece502f454eebab18b81df3bc8d5c,
title = "In situ training with silicon photonics neural networks",
abstract = "Deep learning hardware accelerators based on analog photonic networks are trained on standard digital electronics. We discuss 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 Photonics North, PN 2022 ; Conference date: 24-05-2022 Through 26-05-2022",
year = "2022",
doi = "10.1109/PN56061.2022.9908395",
language = "English (US)",
series = "2022 Photonics North, PN 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 Photonics North, PN 2022",
address = "United States",
}