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Creators/Authors contains: "A. Raj, Z. Wang"

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  1. (, in Proc. European Conference on Optical Communication (ECOC’23) (to appear)
    We present a novel ML framework for modeling the wavelength-dependent gain of multiple EDFAs, based on semi-supervised, self-normalizing neural networks, enabling one-shot transfer learning. Our experiments on 22 EDFAs in Open Ireland and COSMOS testbeds show high-accuracy transfer-learning even when operated across different amplifier types. ©2023 The Author(s) 
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    Accepted Manuscript Full Text Available