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The Gaussian Noise Model Extended to Polarization Dependent Loss and its Application to Outage Probability Estimation.

, , , , , , , and . ECOC, page 1-3. IEEE, (2018)

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The Gaussian Noise Model Extended to Polarization Dependent Loss and its Application to Outage Probability Estimation., , , , , , , and . ECOC, page 1-3. IEEE, (2018)Kerr Nonlinearity Dominance Diagnostic for Polarization-Dependent Loss Impaired Optical Transmissions., , , , and . ECOC, page 1-4. IEEE, (2021)How Uncertainty on the Fiber Span Lengths Influences QoT Estimation using Machine Learning in WDM Networks., , , , , and . OFC, page 1-3. IEEE, (2020)Modelling consumers' expenditure: Italy, 1965-1977, and . European Economic Review, 17 (3): 371--391 (March 1982)Simple self-optimization of WDM networks based on probabilistic constellation shaping Invited., , , , , , , , , and 6 other author(s). JOCN, 12 (1): A82-A94 (2020)The impact of the modulation dependent nonlinear interference missed by the Gaussian noise model., , and . ECOC, page 1-3. IEEE, (2014)Non-marketable assets and households' portfolio choices: A case study of Italy, , and . Journal of Banking & Finance, 17 (6): 1171--1190 (December 1993)Income flexibility and the Frisch conjecture : Evidence from regional data, and . Economics Letters, 22 (1): 7--9 (1986)A Fresh Look at Multicanonical Monte Carlo from a Telecom Perspective., , , , and . GLOBECOM, page 1-8. IEEE, (2009)Machine learning for quality of transmission: a picture of the benefits fairness when planning WDM networks., , , , and . JOCN, 13 (12): 331-346 (2021)