非周期图
计算机科学
人工神经网络
深度学习
功能(生物学)
深层神经网络
人工智能
物理
算法
数学
组合数学
进化生物学
生物
作者
Robert Lupoiu,Mingkun Chen,Yixuan Shao,Chenkai Mao,Jonathan A. Fan
标识
DOI:10.1364/flatoptics.2023.fth1b.3
摘要
Conventional neural network surrogate solvers are severely limited by their inability to function outside of fixed simulation parameters. We present a foundational method for conditioning on arbitrary parameters and demonstrate optimizing high-efficiency aperiodic superpixel deflectors.
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