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Deep Transfer Learning for Nanophotonic Device Design

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Abstract

Applying a transfer-learning technique for generative deep neural networks, we demonstrate a very time-efficient inverse design framework for photonic integrated circuit devices, when there are new demands for structural/material parameters from an existing device library.

© 2022 IEEE

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