Inverse deep learning methods and benchmarks for artificial electromagnetic material design
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DOI: 10.1039/d1nr08346e
Abstract: In this work we investigate the use of deep inverse models (DIMs) for designing artificial electromagnetic materials (AEMs) - such as metamaterials, photonic crystals, and plasmonics - to achieve some desired scattering properties (e.g., transmission… read more here.
Keywords: deep neural; deep learning; design problems; artificial electromagnetic ... See more keywords