Abstract
We present recent advances and future perspectives in using machine learning for characterization, fabrication, and inverse design for device applications, such as hybrid quantum-classical optimization of nanostructures, hypothesis learning for automated discovery, and pre-characterization binning.
© 2022 The Author(s)
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