Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …

We review a novel paradigm that has emerged in analogue neuromorphic optical
computing. The goal is to implement a reservoir computer in optics, where information is …

Optical imaging is commonly used for both scientific and technological applications across
industry and academia. In image sensing, a measurement, such as of an object's position or …

Convolutional neural networks (CNNs) excel in a wide variety of computer vision
applications, but their high performance also comes at a high computational cost. Despite …

Photonic neural network implementation has been gaining considerable attention as a
potentially disruptive future technology. Demonstrating learning in large-scale neural …

We study artificial neural networks with nonlinear waves as a computing reservoir. We
discuss universality and the conditions to learn a dataset in terms of output channels and …

Photonic brain-inspired platforms are emerging as novel analog computing devices,
enabling fast and energy-efficient operations for machine learning. These artificial neural …

Photonics offers exciting opportunities for neuromorphic computing. This paper specifically
reviews the prospects of integrated optical solutions for accelerating inference and training …

Reservoir Computing is a relatively recent computational framework based on a large
Recurrent Neural Network with fixed weights. Many physical implementations of Reservoir …

With the continuous miniaturization of conventional integrated circuits, obstacles such as
excessive cost, increased resistance to electronic motion, and increased energy …