TY - CHAP
T1 - Dimensionality reduction for the on-chip integration of advanced photonic devices and functionalities
AU - Melati, Daniele
AU - Dezfouli, Mohsen Kamandar
AU - Grinberg, Yuri
AU - Al-Digeil, Muhammad
AU - Xu, Dan Xia
AU - Schmid, Jens H.
AU - Cheben, Pavel
AU - Waqas, Abi
AU - Manfredi, Paolo
AU - Zhang, Jianhao
AU - Vivien, Laurent
AU - Alonso-Ramos, Carlos
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Design of modern photonic devices requires to handle a large number of parameters and figures of merit. By scaling down the complexity of the problem, machine learning dimensionality reduction enables the discovery of better performing devices, higher integration scale, and efficient evaluation of fabrication tolerances.
AB - Design of modern photonic devices requires to handle a large number of parameters and figures of merit. By scaling down the complexity of the problem, machine learning dimensionality reduction enables the discovery of better performing devices, higher integration scale, and efficient evaluation of fabrication tolerances.
UR - https://www.scopus.com/pages/publications/85123197655
U2 - 10.1109/ECOC52684.2021.9606084
DO - 10.1109/ECOC52684.2021.9606084
M3 - Chapter
AN - SCOPUS:85123197655
T3 - 2021 European Conference on Optical Communication, ECOC 2021
BT - 2021 European Conference on Optical Communication, ECOC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 European Conference on Optical Communication, ECOC 2021
Y2 - 13 September 2021 through 16 September 2021
ER -