dc.contributor.author | Panayiotou, Tania | en |
dc.contributor.author | Savva, Giannis | en |
dc.contributor.author | Shariati, Behnam | en |
dc.contributor.author | Tomkos, Ioannis | en |
dc.contributor.author | Ellinas, Georgios | en |
dc.coverage.spatial | San Diego | en |
dc.creator | Panayiotou, Tania | en |
dc.creator | Savva, Giannis | en |
dc.creator | Shariati, Behnam | en |
dc.creator | Tomkos, Ioannis | en |
dc.creator | Ellinas, Georgios | en |
dc.date.accessioned | 2021-01-26T09:45:42Z | |
dc.date.available | 2021-01-26T09:45:42Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/63362 | |
dc.description.abstract | We apply deep graph convolutional neural networks for Quality-of-Transmission estimation of unseen network states capturing, apart from other important impairments, the inter-core crosstalk that is prominent in optical networks operating with multicore fibers. | en |
dc.source | 2019 Optical Fiber Communications Conference and Exhibition (OFC) | en |
dc.title | Machine Learning for QoT Estimation of Unseen Optical Network States | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.description.startingpage | 1 | |
dc.description.endingpage | 3 | |
dc.author.faculty | Πολυτεχνική Σχολή / Faculty of Engineering | |
dc.author.department | Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering | |
dc.type.uhtype | Conference Object | en |
dc.contributor.orcid | Ellinas, Georgios [0000-0002-3319-7677] | |
dc.contributor.orcid | Savva, Giannis [0000-0001-5566-1656] | |
dc.contributor.orcid | Tomkos, Ioannis [0000-0001-9721-3405] | |
dc.contributor.orcid | Panayiotou, Tania [0000-0002-4698-9892] | |
dc.gnosis.orcid | 0000-0002-3319-7677 | |
dc.gnosis.orcid | 0000-0001-5566-1656 | |
dc.gnosis.orcid | 0000-0001-9721-3405 | |
dc.gnosis.orcid | 0000-0002-4698-9892 | |