Scalable Machine Learning Models for Optical Transmission System Management

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Publication Date: 4/3/2025

Event: OFC 2025

Reference: M1J.3: 1-3, 2025

Authors: Zehao Wang, Duke University, NEC Laboratories America, Inc.; Agastya Raj, Trinity College; Giacomo Borraccini, NEC Laboratories America, Inc.; Shaobo Han, NEC Laboratories America, Inc.; Yue-Kai Huang, NEC Laboratories America, Inc.; Ting Wang, NEC Laboratories America, Inc.; Marco Ruffini, Trinity College; Dan Kilper, Trinity College; Tingjun Chen, Duke University

Abstract: Optical transmission systems require accurate modeling and performance estimation for autonomous adaption and reconfiguration. We present efficient and scalable machine learning (ML) methods for modeling optical networks at component- and network-level with minimizeddata collection.

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