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Temporal speckle enables probabilistic weights for uncertainty-aware photonic AI
Pernice W +14 more
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Hybrid Training of Optical Neural Networks [PDF]
Optica, 2022 Optical neural networks are emerging as a promising type of machine learning hardware capable of energy-efficient, parallel computation. Today’s optical neural networks are mainly developed to perform optical inference after in silico training on digital simulators.
James Spall +2 more
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Proceedings of the IEEE, 1989
Classical optical information processing and classical neural networks can be adapted and combined to create optical neural networks which offer significant and fundamental advantages over electronic neural networks in various well-defined cases. A systematic morphology of optical neural networks is presented. Special problems they create are discussed.
S K Rogers, H J Caulfield
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Classical optical information processing and classical neural networks can be adapted and combined to create optical neural networks which offer significant and fundamental advantages over electronic neural networks in various well-defined cases. A systematic morphology of optical neural networks is presented. Special problems they create are discussed.
S K Rogers, H J Caulfield
exaly +4 more sources
An optically programmed neural network
IEEE International Conference on Neural Networks, 1988The author report on the design, construction and operation of a hybrid electrooptic computer intended for neural-network applications. They have configured this system to implement what they believe is the largest fully interconnected neural network built to date.
Cary D. Kornfeld +3 more
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Optical Disk Based Neural Network
Applied Optics, 1989The rapid growth of optical disk storage techniques provides an advantage for optics in large capacity information storage and processing. Here we propose an optical disk-based neural network architecture for high speed and large capacity associative processing.
Shudong Wu, F T Yu, Francis T S Yu
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