2.6k citations · 9.9k across the 41 of their papers we have counts for
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Ensemble learning of diffractive optical networks
Md Sadman Sakib Rahman, Jingxi Li, Deniz Mengu +2
A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning. Specifically, there has been a reviva…
Design of Task-Specific Optical Systems Using Broadband Diffractive Neural Networks
Yi Luo, Deniz Mengu, Nezih T. Yardimci +4
We report a broadband diffractive optical neural network design that simultaneously processes a continuum of wavelengths generated by a temporally-incoherent broadband source to al…
Class-specific Differential Detection in Diffractive Optical Neural Networks Improves Inference Accuracy
Jingxi Li, Deniz Mengu, Yi Luo +2
Diffractive deep neural networks have been introduced earlier as an optical machine learning framework that uses task-specific diffractive surfaces designed by deep learning to all…
Response to Comment on "All-optical machine learning using diffractive deep neural networks"
Deniz Mengu, Yi Luo, Yair Rivenson +3
In their Comment, Wei et al. (arXiv:1809.08360v1 [cs.LG]) claim that our original interpretation of Diffractive Deep Neural Networks (D2NN) represent a mischaracterization of the s…
Analysis of Diffractive Optical Neural Networks and Their Integration with Electronic Neural Networks
Deniz Mengu, Yi Luo, Yair Rivenson +1
Optical machine learning offers advantages in terms of power efficiency, scalability and computation speed. Recently, an optical machine learning method based on Diffractive Deep N…
All-Optical Machine Learning Using Diffractive Deep Neural Networks
Xing Lin, Yair Rivenson, Nezih T. Yardimci +3
We introduce an all-optical Diffractive Deep Neural Network (D2NN) architecture that can learn to implement various functions after deep learning-based design of passive diffractiv…