[HTML][HTML] Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip
Optical machine learning has emerged as an important research area that, by leveraging the
advantages inherent to optical signals, such as parallelism and high speed, paves the way …
advantages inherent to optical signals, such as parallelism and high speed, paves the way …
An on-chip photonic deep neural network for image classification
F Ashtiani, AJ Geers, F Aflatouni - Nature, 2022 - nature.com
Deep neural networks with applications from computer vision to medical diagnosis,,,–are
commonly implemented using clock-based processors,,,,,,,–, in which computation speed is …
commonly implemented using clock-based processors,,,,,,,–, in which computation speed is …
[HTML][HTML] Optical coherent dot-product chip for sophisticated deep learning regression
Optical implementations of neural networks (ONNs) herald the next-generation high-speed
and energy-efficient deep learning computing by harnessing the technical advantages of …
and energy-efficient deep learning computing by harnessing the technical advantages of …
Photonic extreme learning machine by free-space optical propagation
Photonic brain-inspired platforms are emerging as novel analog computing devices,
enabling fast and energy-efficient operations for machine learning. These artificial neural …
enabling fast and energy-efficient operations for machine learning. These artificial neural …
Photonic perceptron based on a Kerr Microcomb for high‐speed, scalable, optical neural networks
Optical artificial neural networks (ONNs)—analog computing hardware tailored for machine
learning—have significant potential for achieving ultra‐high computing speed and energy …
learning—have significant potential for achieving ultra‐high computing speed and energy …
[HTML][HTML] An optical neural network using less than 1 photon per multiplication
Deep learning has become a widespread tool in both science and industry. However,
continued progress is hampered by the rapid growth in energy costs of ever-larger deep …
continued progress is hampered by the rapid growth in energy costs of ever-larger deep …
[HTML][HTML] In-memory photonic dot-product engine with electrically programmable weight banks
Electronically reprogrammable photonic circuits based on phase-change chalcogenides
present an avenue to resolve the von-Neumann bottleneck; however, implementation of …
present an avenue to resolve the von-Neumann bottleneck; however, implementation of …
[HTML][HTML] Photonic machine learning with on-chip diffractive optics
Abstract Machine learning technologies have been extensively applied in high-performance
information-processing fields. However, the computation rate of existing hardware is …
information-processing fields. However, the computation rate of existing hardware is …
[HTML][HTML] Quantum-noise-limited optical neural networks operating at a few quanta per activation
A practical limit to energy efficiency in computation is ultimately from noise, with quantum
noise [1] as the fundamental floor. Analog physical neural networks [2], which hold promise …
noise [1] as the fundamental floor. Analog physical neural networks [2], which hold promise …
All-optical machine learning using diffractive deep neural networks
Deep learning has been transforming our ability to execute advanced inference tasks using
computers. Here we introduce a physical mechanism to perform machine learning by …
computers. Here we introduce a physical mechanism to perform machine learning by …