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03/03/2023
Machine learning using magnetic stochastic synapses
The impressive performance of artificial neural networks has come at the...
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12/09/2022
A perspective on physical reservoir computing with nanomagnetic devices
Neural networks have revolutionized the area of artificial intelligence ...
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11/29/2021
Quantifying the Computational Capability of a Nanomagnetic Reservoir Computing Platform with Emergent Magnetization Dynamics
Arrays of interconnected magnetic nano-rings with emergent magnetization...
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10/11/2021
EchoVPR: Echo State Networks for Visual Place Recognition
Recognising previously visited locations is an important, but unsolved, ...
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02/23/2021
A Robotic Model of Hippocampal Reverse Replay for Reinforcement Learning
Hippocampal reverse replay is thought to contribute to learning, and par...
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01/11/2021
Exploiting Multiple Timescales in Hierarchical Echo State Networks
Echo state networks (ESNs) are a powerful form of reservoir computing th...
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04/30/2020
Memristors – from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing
Machine learning, particularly in the form of deep learning, has driven ...
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03/16/2020
A semi-supervised sparse K-Means algorithm
We consider the problem of data clustering with unidentified feature qua...
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12/04/2019
SpaRCe: Sparse reservoir computing
"Sparse" neural networks, in which relatively few neurons or connections...
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08/26/2019
An empirical comparison between stochastic and deterministic centroid initialisation for K-Means variations
K-Means is one of the most used algorithms for data clustering and the u...
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07/19/2019
Learning sparsity in reservoir computing through a novel bio-inspired algorithm
The mushroom body is the key network for the representation of learned o...
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11/20/2017
A generalised framework for detailed classification of swimming paths inside the Morris Water Maze
The Morris Water Maze is commonly used in behavioural neuroscience for t...
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10/12/2017
