{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T16:35:29Z","timestamp":1783096529955,"version":"3.54.6"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Union","doi-asserted-by":"publisher","award":["PE00000001"],"award-info":[{"award-number":["PE00000001"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,28]]},"DOI":"10.1109\/icc45041.2023.10278767","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T17:54:10Z","timestamp":1698083650000},"page":"441-446","source":"Crossref","is-referenced-by-count":10,"title":["Uncertainty-Aware QoT Forecasting in Optical Networks with Bayesian Recurrent Neural Networks"],"prefix":"10.1109","author":[{"given":"Nicola","family":"Di Cicco","sequence":"first","affiliation":[{"name":"Politecnico di Milano,Department of Electronics, Information and Bioengineering (DEIB),Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacopo","family":"Talpini","sequence":"additional","affiliation":[{"name":"University of Milano-Bicocca,Department of Informatics, Systems and Communication (DISCo),Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00ebm\u00ebdhe","family":"Ibrahimi","sequence":"additional","affiliation":[{"name":"Politecnico di Milano,Department of Electronics, Information and Bioengineering (DEIB),Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Savi","sequence":"additional","affiliation":[{"name":"University of Milano-Bicocca,Department of Informatics, Systems and Communication (DISCo),Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Massimo","family":"Tornatore","sequence":"additional","affiliation":[{"name":"Politecnico di Milano,Department of Electronics, Information and Bioengineering (DEIB),Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2018.2880039"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/BalkanCom55633.2022.9900791"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1364\/JOCN.410694"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1364\/JOCN.438269"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2019.8845132"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2022.3160379"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1364\/NETWORKS.2020.NeM3B.1"},{"issue":"4","key":"ref8","doi-asserted-by":"crossref","first-page":"B60","DOI":"10.1364\/JOCN.417434","article-title":"Machine learning techniques for quality of transmission estimation in optical networks","volume":"13","author":"Pointurier","year":"2021","journal-title":"J. Opt. Commun. Netw."},{"key":"ref9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1364\/OFC.2021.F3B.2","article-title":"Field trial of vibration detection and localization using coherent telecom transponders over 380-km link","volume-title":"2021 Optical Fiber Communications Conference and Exhibition (OFC)","author":"Wellbrock","year":"2021"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2987443.2987483"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1364\/JOCN.8.000A45"},{"key":"ref12","first-page":"1","article-title":"Evaluation of elastic modulation gains in microsofts optical backbone in north america","volume-title":"2016 Optical Fiber Communications Conference and Exhibition (OFC)","author":"Ghobadi","year":"2016"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1364\/OFC.2021.Th4J.5","article-title":"Forecasting lightpath qot with deep neural networks","volume-title":"2021 Optical Fiber Communications Conference and Exhibition (OFC)","author":"Chouman","year":"2021"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1364\/OFC.2020.W2A.24","article-title":"Recurrent neural networks for short-term forecast of lightpath performance","volume-title":"2020 Optical Fiber Communications Conference and Exhibition (OFC)","author":"Aladin","year":"2020"},{"key":"ref15","first-page":"1","article-title":"Deep learning for multi-step performance prediction in operational optical networks","volume-title":"2020 Conference on Lasers and Electro-Optics (CLEO)","author":"Mezni","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2021.3110513"},{"key":"ref17","first-page":"1050","article-title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning","volume-title":"international conference on machine learning","author":"Gal"},{"key":"ref18","first-page":"4697","article-title":"Bayesian deep learning and a probabilistic perspective of generalization","volume":"33","author":"Wilson","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref19","first-page":"1613","article-title":"Weight uncertainty in neural network","volume-title":"International conference on machine learning","author":"Blundell"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2017.19"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1162\/089976600300015015"},{"key":"ref22","article-title":"Sequence to sequence learning with neural networks","volume":"27","author":"Sutskever","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref23","article-title":"A theoretically grounded application of dropout in recurrent neural networks","volume":"29","author":"Gal","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2020.3022107"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177703732"},{"key":"ref27","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume-title":"Proceedings of the 33rd International Conference on Neural Information Processing Systems","author":"Paszke","year":"2019"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511791277"}],"event":{"name":"ICC 2023 - IEEE International Conference on Communications","location":"Rome, Italy","start":{"date-parts":[[2023,5,28]]},"end":{"date-parts":[[2023,6,1]]}},"container-title":["ICC 2023 - IEEE International Conference on Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10278505\/10278554\/10278767.pdf?arnumber=10278767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T08:56:03Z","timestamp":1709369763000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10278767\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,28]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/icc45041.2023.10278767","relation":{},"subject":[],"published":{"date-parts":[[2023,5,28]]}}}