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Data-efficient Modeling of Optical Matrix Multipliers Using Transfer Learning
Published 29 Nov 2022 in cs.LG, cs.ET, and cs.NE | (2211.16038v1)
Abstract: We demonstrate transfer learning-assisted neural network models for optical matrix multipliers with scarce measurement data. Our approach uses <10\% of experimental data needed for best performance and outperforms analytical models for a Mach-Zehnder interferometer mesh.
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