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. 2019 Feb 4;9:1368. doi: 10.1038/s41598-018-37952-2

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Spectrum approximation using deep ResNet. We use 16,000 (80% of the total) input data for training and 4,000 (20% of the total) data for testing. a, b, and c are comparison of ResNet predicted spectral response of the three representative power splitters to the numerically verified spectral responses. Black, blue, and red colors stand for transmission at port 1, transmission at port 2, and reflection at the input port, respectively. Solid lines are true values for a given hole vector and dashed lines are predicted spectral response using ResNet.