activity
20172021
most citedReinforcement Learning in a large scale photonic Recurrent Neural Network

407 citations · 463 across the 5 of their papers we have counts for

collaborators

6 papers

cs.ET2021

Ultrafast Neuromorphic Photonic Image Processing with a VCSEL Neuron

Joshua Robertson, Paul Kirkland, Juan Arturo Alanis +4

The ever-increasing demand for Artificial Intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors ar…

physics.optics2020★ 5 cited

All-optical neuromorphic binary convolution with a spiking VCSEL neuron for image gradient magnitudes

Yahui Zhang, Joshua Robertson, Shuiying Xiang +3

All-optical binary convolution with a photonic spiking vertical-cavity surface-emitting laser (VCSEL) neuron is proposed and demonstrated experimentally for the first time. Optical…

eess.IV2020★ 1 cited

Convolutional Image Edge Detection Using Ultrafast Photonic Spiking VCSEL Neurons

Joshua Robertson, Yahui Zhang, Matej Hejda +4

We report experimentally and in theory on the detection of edge information in digital images using ultrafast spiking optical artificial neurons towards convolutional neural networ…

eess.SP2018★ 50 cited

PAM-4 Transmission at 1550nm using Photonic Reservoir Computing Post-processing

Apostolos Argyris, Julián Bueno, Ingo Fischer

The efficacy of data decoding in contemporary ultrafast fiber transmission systems is greatly determined by the capabilities of the signal processing tools that are used. The recei…

cs.NE2017★ 407 cited

Reinforcement Learning in a large scale photonic Recurrent Neural Network

Julian Bueno, Sheler Maktoobi, Luc Froehly +4

Photonic Neural Network implementations have been gaining considerable attention as a potentially disruptive future technology. Demonstrating learning in large scale neural network…

eess.SP2017

Photonic machine learning implementation for signal recovery in optical communications

Apostolos Argyris, Julián Bueno, Ingo Fischer

Machine learning techniques have proven very efficient in assorted classification tasks. Nevertheless, processing time-dependent high-speed signals can turn into an extremely chall…