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- W3201311145 abstract "Abstract We report a neural network model for predicting the electromagnetic response of mesoscale metamaterials as well as generate design parameters for a desired spectral behavior. Our approach entails treating spectral data as time-varying sequences and the inverse problem as a single-input multiple output model, thereby compelling the network architecture to learn the geometry of the metamaterial designs from the spectral data in lieu of abstract features." @default.
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- W3201311145 date "2021-09-20" @default.
- W3201311145 modified "2023-10-17" @default.
- W3201311145 title "Leveraging long short-term memory (LSTM)-based neural networks for modeling structure–property relationships of metamaterials from electromagnetic responses" @default.
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- W3201311145 doi "https://doi.org/10.1038/s41598-021-97999-6" @default.
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