
Some Theoretical Properties of a Network of Discretely Firing Neurons
The problem of optimising a network of discretely firing neurons is addr...
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SelfOrganising Stochastic Encoders
The processing of megadimensional data, such as images, scales linearly...
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The Development of Dominance Stripes and Orientation Maps in a SelfOrganising Visual Cortex Network (VICON)
A selforganising neural network is presented that is based on a rigorou...
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Stochastic Vector Quantisers
In this paper a stochastic generalisation of the standard LindeBuzoGra...
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Adaptive Cluster Expansion (ACE): A Multilayer Network for Estimating Probability Density Functions
We derive an adaptive hierarchical method of estimating high dimensional...
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Modelling the Probability Density of Markov Sources
This paper introduces an objective function that seeks to minimise the a...
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Discrete Network Dynamics. Part 1: Operator Theory
An operator algebra implementation of Markov chain Monte Carlo algorithm...
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SelfOrganised Factorial Encoding of a Toroidal Manifold
It is shown analytically how a neural network can be used optimally to e...
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Adaptive Cluster Expansion (ACE): A Hierarchical Bayesian Network
Using the maximum entropy method, we derive the "adaptive cluster expans...
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Invariant Stochastic Encoders
The theory of stochastic vector quantisers (SVQ) has been extended to al...
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Using Stochastic Encoders to Discover Structure in Data
In this paper a stochastic generalisation of the standard LindeBuzoGra...
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Using SelfOrganising Mappings to Learn the Structure of Data Manifolds
In this paper it is shown how to map a data manifold into a simpler form...
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Stephen Luttrell
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Independent Researcher, Basic Research at QinetiQ Group PLC from 19822010, PhD, Theoretical Physics at Cambridge University 19751982