Search Results - "Hart, Allen G."

A hidden Markov model for describing turbostratic disorder applied to carbon blacks and graphene by Hart, Allen G., Hansen, Thomas C., Kuhs, Werner F.

“…A mathematical framework is presented to represent turbostratic disorder in materials like carbon blacks, smectites and twisted n‐layer graphene. In…”
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Generalised synchronisations, embeddings, and approximations for continuous time reservoir computers by Hart, Allen G.

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Echo State Networks trained by Tikhonov least squares are L 2 ( μ ) approximators of ergodic dynamical systems by Hart, Allen G., Hook, James L., Dawes, Jonathan H.P.

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Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems by Hart, Allen G., Hook, James L., Dawes, Jonathan H.P.

“…Echo State Networks (ESNs) are a class of single-layer recurrent neural networks with randomly generated internal weights, and a single layer of tuneable outer…”
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Generalised Synchronisations, Embeddings, and Approximations for Continuous Time Reservoir Computers by Hart, Allen G

“…We establish conditions under which a continuous time reservoir computer, such as a leaky integrator echo state network, admits a generalised synchronisation…”
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(Thesis) Reservoir Computing With Dynamical Systems by Hart, Allen G

“…A reservoir computer is a special type of neural network, where most of the weights are randomly fixed and only a subset are trained. In this thesis we prove…”
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Echo State Networks trained by Tikhonov least squares are L2({\mu}) approximators of ergodic dynamical systems by Hart, Allen G, Hook, James L, Dawes, Jonathan H P

“…Echo State Networks (ESNs) are a class of single-layer recurrent neural networks with randomly generated internal weights, and a single layer of tuneable outer…”
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A Markov theoretic description of stacking disordered aperiodic crystals including ice and opaline silica by Hart, Allen G, Hansen, Thomas C, Kuhs, Werner F

“…July 2018 Acta Crystallographica Section A: Foundations and Advances 74(4):357-372 We review the Markov theoretic description of 1D aperiodic crystals,…”
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Embedding and Approximation Theorems for Echo State Networks by Hart, Allen G, Hook, James L, Dawes, Jonathan H P

“…Echo State Networks (ESNs) are a class of single layer recurrent neural networks that have enjoyed recent attention. In this paper we prove that a suitable…”
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Using Echo State Networks to Approximate Value Functions for Control by Hart, Allen G, Olding, Kevin R, Cox, A. M. G, Isupova, Olga, Dawes, J. H. P

“…An Echo State Network (ESN) is a type of single-layer recurrent neural network with randomly-chosen internal weights and a trainable output layer. We prove…”
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