| DOI | Resolve DOI: https://doi.org/10.1109/ECOC52684.2021.9606084 |
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| Author | Search for: Melati, Daniele; Search for: Dezfouli, Mohsen Kamandar; Search for: Grinberg, Yuri1; Search for: Al-Digeil, Muhammad1; Search for: Xu, Dan-Xia2; Search for: Schmid, Jens H.2; Search for: Cheben, Pavel2; Search for: Waqas, Abi; Search for: Manfredi, Paolo; Search for: Zhang, Jianhao; Search for: Vivien, Laurent; Search for: Alonso-Ramos, Carlos |
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| Affiliation | - National Research Council of Canada. Digital Technologies
- National Research Council of Canada. Advanced Electronics and Photonics
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| Format | Text, Article |
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| Conference | 2021 European Conference on Optical Communication (ECOC), Sept 13-16, 2021, Bordeaux, France |
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| Subject | dimensionality reduction; performance evaluation; fabrication; Europe; optical fiber communication; complexity theory; system-on-chip |
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| Abstract | 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. |
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| Publication date | 2021-11-22 |
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| Publisher | IEEE |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | c0deca8b-b9c5-4b87-8e69-53ed37d8295c |
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| Record created | 2022-05-09 |
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| Record modified | 2022-05-11 |
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