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Showing 1–5 of 5 results
Advanced filters: Author: Ilker Oguz Clear advanced filters

  • Methods to train physical neural networks, such as backpropagation-based and backpropagation-free approaches, are explored to allow scaling up of artificial intelligence models far beyond present small-scale laboratory demonstrations, potentially enhancing computational efficiency.

    • Ali Momeni
    • Babak Rahmani
    • Romain Fleury
    Reviews
    Nature
    Volume: 645, P: 53-61

  • Multiple scattering capable of synthesizing programmable linear and nonlinear transformations concurrently at low optical power in the order of milliwatts continuous-wave power for optical computing is demonstrated, paving the way for ultra-efficient, low-power all-optical neural networks.

    • Mustafa Yildirim
    • Niyazi Ulas Dinc
    • Christophe Moser
    ResearchOpen Access
    Nature Photonics
    Volume: 18, P: 1076-1082

  • Optical computing promises high-speed computations but presents challenges in nonlinear information processing. This Article demonstrates a scalable and energy-efficient nonlinear optical-computing framework that can perform machine learning tasks.

    • Uğur Teğin
    • Mustafa Yıldırım
    • Demetri Psaltis
    Research
    Nature Computational Science
    Volume: 1, P: 542-549