322 citations · 556 across the 15 of their papers we have counts for
15 papers
Reproducible Reservoir Computing with Thermally Driven Superparamagnets: Controlling Temperature Sensitivity
Zhengfei Chen, Alex Welbourne, Matthew O. A. Ellis +3
Unconventional computing systems must demonstrate robust performance under real-world environmental conditions to enable practical deployments. We have recently proposed superparam…
RingSim- An Agent-based Approach for Modelling Mesoscopic Magnetic Nanowire Networks
Ian T Vidamour, Guru Venkat, Charles Swindells +9
We describe 'RingSim', a phenomenological agent-based model that allows numerical simulation of magnetic nanowire networks with areas of hundreds of micrometers squared for duratio…
Magnetic domain walls : Types, processes and applications
G. Venkat, D. A. Allwood, T. J. Hayward
Domain walls (DWs) in magnetic nanowires are promising candidates for a variety of applications including Boolean/unconventional logic, memories, in-memory computing as well as mag…
Machine learning using magnetic stochastic synapses
Matthew O. A. Ellis, Alex Welbourne, Stephan J. Kyle +4
The impressive performance of artificial neural networks has come at the cost of high energy usage and CO emissions. Unconventional computing architectures, with magnetic syste…
A perspective on physical reservoir computing with nanomagnetic devices
Dan A Allwood, Matthew O A Ellis, David Griffin +11
Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this succ…
Reconfigurable Reservoir Computing in a Magnetic Metamaterial
Ian Vidamour, Charles Swindells, Guru Venkat +10
In-materia reservoir computing (RC) leverages the intrinsic physical responses of functional materials to perform complex computational tasks. Magnetic metamaterials are exciting c…