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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 minimized data collection.more » « lessFree, publicly-accessible full text available March 30, 2026
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Raj, Agastya; Kilper, Dan; Ruffini, Marco (, IEEE)
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Raj, Agastya; Wang, Zehao; Slyne, Frank; Chen, Tingjun; Kilper, Dan; Ruffini, Marco (, 50th European Conference on Optical Communication)
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Raj, Agastya; Wang, Zehao; Slyne, Frank; Chen, Tingjun; Kilper, Dan; Ruffini, Marco (, 50th European Conference on Optical Communication)
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