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Now showing items 41-50 of 185
Optimization of neuronal morphologies for pattern recognition
(2010)
Poster presented at CNS 2010
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 application of feature selection to the development of Gaussian process models for percutaneous absorption.
(2010)
Objectives: The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical ...
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 ...
Software defect prediction using static code metrics underestimates defect-proneness
(Institute of Electrical and Electronics Engineers (IEEE), 2010)
Many studies have been carried out to predict the presence of software code defects using static code metrics. Such studies typically report how a classifier performs with real world data, but usually no analysis of the ...
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 application of Gaussian processes in the prediction of percutaneous absorption
(2009-09)
Objectives The aim was to assess mathematically the nature of a skin permeability dataset and to determine the utility of Gaussian processes in developing a predictive model for skin permeability, comparing it with existing ...