Utilizing Mixed Training and Multi-Head Attention to Address Data Shift in AI-Based Electromagnetic Solvers for Nano-Structured Metamaterials

When designing nano-structured metamaterials with an iterative optimization method, a fast deep learning solver is desirable to replace a time-consuming numerical solver, and the related issue of data shift is a subtle yet easily overlooked challenge. In this work, we explore the data shift challeng...

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Detalles Bibliográficos
Autores principales: Zeng, Zhenjia, Wang, Lei, Wu, Yiran, Hu, Zhipeng, Evans, Julian, Zhu, Xinhua, Ye, Gaoao, He, Sailing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10609168/
https://www.ncbi.nlm.nih.gov/pubmed/37887929
http://dx.doi.org/10.3390/nano13202778

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10609168/
https://www.ncbi.nlm.nih.gov/pubmed/37887929
http://dx.doi.org/10.3390/nano13202778

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