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Now showing items 11-20 of 93
Predicting drug absorption rates through human skin
(Institute of Electrical and Electronics Engineers (IEEE), 2010)
Predicting the rate at which a substance will pass through human skin and into the bloodstream is a problem of current interest. We use Gaussian Process modeling to train a set of predictors using every combination of six ...
The effect of non-specific LTD on pattern recognition in cerebellar Purkinje cells
(2010)
Poster presented at CNS 2010
Photometric redshift estimation using Gaussian processes
(2010)
We present a comparison between Gaussian processes (GPs) and artificial neural networks (ANNs) as methods for determining photometric redshifts for galaxies, given training-set data. In particular, we compare their degradation ...
Using randomised vectors in transcription factor binding site predictions
(Institute of Electrical and Electronics Engineers (IEEE), 2010)
Finding the location of binding sites in DNA is a difficult problem. Although the location of some binding sites have been experimentally identified, other parts of the genome may or may not contain binding sites. This ...
Evolution of bistable dynamics in spiking neural controllers for agents performing olfactory attraction and aversion
(2010)
Poster presented at CNS 2010
Correcting Errors in Optical Data Transmission Using Neural Networks
(2010)
Optical data communication systems are prone to a variety of processes that modify the transmitted signal, and contribute errors in the determination of 1s from 0s. This is a difficult, and commercially important, problem ...
The Effect of Different Forms of Synaptic Plasticity on Pattern Recognition in the Cerebellar Cortex
(2009)
Many cerebellar learning theories assume that long-term depression (LTD) of synapses between parallel fibres (PFs) and Purkinje cells (PCs) provides the basis for pattern recognition in the cerebellum. Previous work has ...
Connection Strategies in Associative Memory Models
(2009)
The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so results in artificial ...
Evolution of bilateral symmetry in agents controlled by spiking neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 2009)
We present in this paper three novel developmental models allowing information to be encoded in space and time, using spiking neurons placed on a 2D substrate. In two of these models, we introduce neural development that ...