Physics-Informed Gaussian Process Regression for Optical Fiber Communication Systems

We present a framework for enhancing Gaussian process regression machine learning models with a priori knowledge derived from models of the transmission physics in optical networks. This is done by framing the regression problem as multi-task learning, in which both the measured data and targets der...

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