Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models
2020
We designed mirrored plasmonic filters using an advanced active machine learning algorithm that efficiently explores multiple physical models with different approximation fidelities and costs. This method is applicable to a variety of nanophotonics optimization problems.
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