5 papers
Terahertz Pulse Shaping Using Diffractive Surfaces
Muhammed Veli, Deniz Mengu, Nezih T. Yardimci +5
Recent advances in deep learning have been providing non-intuitive solutions to various inverse problems in optics. At the intersection of machine learning and optics, diffractive…
Spectrally-Encoded Single-Pixel Machine Vision Using Diffractive Networks
Jingxi Li, Deniz Mengu, Nezih T. Yardimci +6
3D engineering of matter has opened up new avenues for designing systems that can perform various computational tasks through light-matter interaction. Here, we demonstrate the des…
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…
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…
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…