@inproceedings{ab8f954ae7ea45b29dfb7f431cb3ce29,
title = "Silicon Photonics for Machine Learning: Training and Inference",
abstract = "Photonics neural networks employ optical device physics for neuron models, and optical interconnects for distributed, parallel, and analog processing for high-bandwidth, low-latency, and low-switching energy applications in AI and neuromorphic computing. We discuss silicon photonics for machine learning acceleration for inference and in situ training.",
author = "Shastri, \{B. J.\} and Filipovich, \{M. J.\} and Z. Guo and Prucnal, \{P. R.\} and C. Huang and Tait, \{A. N.\} and S. Shekhar and Sorger, \{V. J.\}",
note = "Publisher Copyright: {\textcopyright} 2022 Optica.; 2022 European Conference on Optical Communication, ECOC 2022 ; Conference date: 18-09-2022 Through 22-09-2022",
year = "2022",
language = "English (US)",
series = "2022 European Conference on Optical Communication, ECOC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 European Conference on Optical Communication, ECOC 2022",
address = "United States",
}