N. Davey

Neil Davey, Rod Adams, Wanida Pensuwon, 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

The Effects of Changing the Update Threshold in High Capacity Associative Memory Model

Weiliang Chen, N. Davey, R. Adams, 2006 .

Using Varying Negative Examples to Improve Computational Predictions of Transcription Factor Binding Sites

Neil Davey, Mark Robinson, Yi Sun, 2012, EANN.

Effect of Using Varying Negative Examples in Transcription Factor Binding Site Predictions

Neil Davey, Mark Robinson, Yi Sun, 2011, EvoBio.

Using real-valued meta classifiers to integrate binding site predictions

Yi Sun, N. Davey, M. Robinson, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Attention mechanisms and component-based face detection

Neil Davey, Yi Sun, J. W. Han, 2009, 2009 Proceeding of International Conference on Methods and Models in Computer Science (ICM2CS).

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Silvestro Micera, Johannes Schemmel, Szabolcs Káli, 2017, BMC Neuroscience.

Design and Use of Neural Network Applications in Telecommunications

Ray J. Frank, Neil Davey, S. Hunt, 2018, Computational Intelligence in Telecommunications Networks.

The Architecture and Performance of a Stochastic Competitive Evolutionary Neural Tree Network

Neil Davey, Rod Adams, Stella J. George, 2004, Applied Intelligence.

Hierarchical classification with a competitive evolutionary neural tree

Neil Davey, Rod Adams, Kate Butchart, 1999, Neural Networks.

Hierarchical classification with a stochastic competitive evolutionary neural tree

Neil Davey, Rod Adams, Kate Butchart, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

A Comparative Study of two Self Organising and Structurally Adaptive Dynamic Neural Tree Networks

Neil Davey, Roger Adams, Kate Butchart, 1995 .

Using pre & post-processing methods to improve binding site predictions

Neil Davey, Mark Robinson, Yi Sun, 2009, Pattern Recognit..

Human Face Recognition using Soft Computing RBF

N. Davey, W. Pensuwon, R.G. Adams, 2006, TENCON 2006 - 2006 IEEE Region 10 Conference.

Improving Radial Basis Function Networks for Human Face Recognition Using a Soft Computing Approach

Neil Davey, Rod Adams, Wiroj Taweepworadej, 2006, SEAL.

Optimization of neuronal morphologies for pattern recognition

Neil Davey, Reinoud Maex, Volker Steuber, 2010, BMC Neuroscience.

The Effect of Different Forms of Synaptic Plasticity on Pattern Recognition in the Cerebellar Cortex

Neil Davey, Rod Adams, Giseli de Sousa, 2009, ICANNGA.

Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise

Neil Davey, Reinoud Maex, Volker Steuber, 2017, Scientific Reports.

Representations and Character Recognition: An Issue for Action in Perception

Fiona M. Richardson, S. H. Anthony, N. Davey, 2019, Proceedings of EuroCogSci 03.

Dendritic morphology predicts pattern recognition performance in multi-compartmental model neurons with and without active conductances

Neil Davey, Rod Adams, Giseli de Sousa, 2014, Journal of Computational Neuroscience.

Mining Hubble Space Telescope images

Neil Davey, Yi Sun, James E. Geach, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Time Series Prediction and Neural Networks

Neil Davey, Ray J. Frank, Stephen P. Hunt, 2001, J. Intell. Robotic Syst..

The potential for student performance prediction in small cohorts with minimal available attributes

Neil Davey, Edward Wakelam, Amanda Jefferies, 2019, Br. J. Educ. Technol..

The role of lateral inhibition in the sensory processing in a simulated spiking neural controller for a robot

Neil Davey, Rod Adams, Lola Cañamero, 2009, 2009 IEEE Symposium on Artificial Life.

Evolution of bilateral symmetry in agents controlled by spiking neural networks

Neil Davey, Rod Adams, Lola Cañamero, 2009, 2009 IEEE Symposium on Artificial Life.

The development of a software clone detector

Neil Davey, Ray J. Frank, Dennis Stewart William Tansley, 1995 .

Formal Systems, Not Methods

Bruce Christianson, Neil Davey, Martin Loomes, 2004, TFM.

A reward driven connectionist model of cognitive development

D. Messer, N. Davey, Pam Smith, 1999 .

Gender Classification of Face Images: The Role of Global and Feature-Based Information

Neil Davey, Tim M. Gale, Martin Loomes, 2004, ICONIP.

The /s/ morpheme and the compounding phenomenon in English

Neil Davey, Victoria A. Murphy, Pamela Smith, 2019, Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society.

HOW THE CONSTRAINTS ON ENGLISH COMPOUND PRODUCTION MIGHT BE LEARNT FROM THE LINGUISTIC INPUT: EVIDENCE FROM SIMPLE RECURRENT NETWORKS

Neil Davey, Victoria A. Murphy, Pamela Smith, 2004 .

Why will rat's go where rats will not?

Neil Davey, Victoria Murphy, Jenny Hayes, 2002, ESANN.

Plural morphology in compounding is not good evidence to support the dual mechanism model

Neil Davey, Victoria A. Murphy, L. Peters, 2001 .

The Effect of Different Types of Synaptic Plasticity on the Performance of Associative Memory Networks with Excitatory and Inhibitory Sub-populations

Neil Davey, Rod Adams, Reinoud Maex, 2012, IPCAT.

High capacity, small world associative memory models

Neil Davey, Rod Adams, Lee Calcraft, 2006, Connect. Sci..

High capacity associative memories and connection constraints

Neil Davey, Rod Adams, N. Davey, 2004, Connect. Sci..

High Capacity Recurrent Associative Memories

Neil Davey, Rod Adams, Stephen P. Hunt, 2002, Neurocomputing.

High capacity associative memory models - binary and bipolar representation

Neil Davey, S. Hunt, Roger Adams, 2004 .

A comparative analysis of high performance associative memory models.

N. Davey, S. P. Hunt, N. Davey, 2000 .

High performance associative memory models and symmetric connections

Neil Davey, S. Hunt, Roger Adams, 2000 .

The Capacity and Attractor Basins of Associative Memory Models

Neil Davey, Stephen P. Hunt, N. Davey, 1999, IWANN.

Further thoughts on precision

Bruce Christianson, Neil Davey, Yi Sun, 2011, EASE.

Input window size and neural network predictors

Neil Davey, Ray J. Frank, Stephen P. Hunt, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

A Modular Attractor Model of Semantic Access

Neil Davey, Ray J. Frank, William Power, 1999, IWANN.

Categorizing facial expressions: a comparison of computational models

Neil Davey, Aruna Shenoy, Ray J. Frank, 2011, Neural Computing and Applications.

Evolved Patterns of Connectivity in Associative Memory Models

Neil Davey, Rod Adams, Lee Calcraft, 2006, 2006 5th IEEE International Conference on Cognitive Informatics.

Evolving high capacity associative memories with efficient wiring

N. Davey, R. Adams, L. Calcraft, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Using a genetic algorithm to investigate efficient connectivity in associative memories

Neil Davey, Rod Adams, Lee Calcraft, 2009, Neurocomputing.

EvolvingHigh CapacityAssociative Memories with EfficientWiring

Neil Davey, N. Davey, 2005 .

Unsupervised learning with normalised data and non-Euclidean norms

Neil Davey, Rod Adams, Kevin Doherty, 2007, Appl. Soft Comput..

Using Machine Learning Techniques to Recover Prismatic Cirrus Ice Crystal Size from 2-Dimensional Light Scattering Patterns

Neil Davey, Yi Sun, Mauro Roisenberg, 2016, ICANN.

The Correlation between EEG Signals as Measured in Different Positions on Scalp Varying with Distance

Neil Davey, Yi Sun, Na Helian, 2018, BICA.

Designing & developing QueBall, a robotic device for autism therapy

Neil Davey, François Michaud, Tamie Salter, 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

The application of Gaussian processes in the prediction of percutaneous absorption

Neil Davey, Marc B. Brown, Yi Sun, 2009, ESANN.

Spiking Neural Network Controllers Evolved for Animat Foraging Based on Temporal Pattern Recognition in the Presence of Noise on Input

Neil Davey, Borys Wróbel, Volker Steuber, 2018, ICANN.

Evolving spiking neural networks to control animats for temporal pattern recognition and foraging

Neil Davey, Borys Wróbel, Volker Steuber, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

volving Spiking Neural Networks for Temporal Pattern Recognition in the Presence of Noise

Neil Davey, Borys Wróbel, Volker Steuber, 2014, ALIFE.

A potential role for the cerebellar nuclei in absence seizures

V. Steuber, R. Maex, C. D. De Zeeuw, 2013, BMC Neuroscience.

Connectivity graphs and the performance of sparse associative memory models

Neil Davey, Rod Adams, Volker Steuber, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

High Performance Associative Memory Models with Low Wiring Costs

N. Davey, R. Adams, L. Calcraft, 2006, 2006 3rd International IEEE Conference Intelligent Systems.

THE CONNECTIVITY AND PERFORMANCE OF SMALL-WORLD AND MODULAR ASSOCIATIVE MEMORY MODELS

Neil Davey, Roger Adams, Volker Steuber, 2008 .

Locally-Connected and Small-World Associative Memories in Large Networks

Neil Davey, Roger Adams, Lee Calcraft, 2006 .

Combining experts in order to identify binding sites in yeast and mouse genomic data

Neil Davey, Mark Robinson, Yi Sun, 2008, Neural Networks.

Combining experts in order to identify binding sites in genomic data

Neil Davey, Mark Robinson, Roger Adams, 2008 .

Recognizing facial expressions: Computational models and humans

Neil Davey, Aruna Shenoy, Ray J. Frank, 2013, 2013 13th UK Workshop on Computational Intelligence (UKCI).

Recognizing emotions by analyzing facial expressions

Neil Davey, Aruna Shenoy, Tim M. Gale, 2007 .

Visual crowding and category specific deficits for pictorial stimuli: A neural network model

Tim M. Gale, Ray J. Frank, N. Davey, 2001, Cognitive neuropsychology.

Development of a Gaussian Process – feature selection model to characterise (poly)dimethylsiloxane (Silastic®) membrane permeation

Neil Davey, Yi Sun, Mark Hewitt, 2020, The Journal of pharmacy and pharmacology.

Improving Transcription Factor Binding Site Predictions by Using Randomised Negative Examples

Neil Davey, Mark Robinson, Yi Sun, 2012, IPCAT.

Biologically plausible computational models for facial expression recognition

Neil Davey, Aruna Shenoy, Ray Frank, 2013, 2013 5th Computer Science and Electronic Engineering Conference (CEEC).

Discriminating Angry, Happy and Neutral Facial Expression: A Comparison of Computational Models

Neil Davey, Aruna Shenoy, Ray J. Frank, 2009, EANN.

Representation and classification of facial expression in a modular computational model

Ray J. Frank, Neil Davey, Aruna Shenoy, 2009 .

Recognizing Facial Expressions: A Comparison of Computational Approaches

Bruce Christianson, Neil Davey, Aruna Shenoy, 2008, ICANN.

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression

Neil Davey, Yi Sun, Parivash Ashrafi, 2018, The Journal of pharmacy and pharmacology.

An Investigation of How Wavelet Transform Can Affect the Correlation Performance of Biomedical Signals - The Correlation of EEG and HRV Frequency Bands in the Frontal Lobe of the Brain

Neil Davey, Yi Sun, Na Helian, 2018, BIOSIGNALS.

From evolving artificial gene regulatory networks to evolving spiking neural networks for pattern recognition

Neil Davey, Borys Wróbel, Volker Steuber, 2013, BMC Neuroscience.

Self-organising map representations of greyscale images reflect human similarity judgements

N. Davey, R.J. Frank, T.M. Gale, 2004, 2004 2nd International IEEE Conference on 'Intelligent Systems'. Proceedings (IEEE Cat. No.04EX791).

N. Davey, T. Gale, R. Frank, 2002, Brain and Cognition.

The detection of fraud in mobile phone networks

Ray J. Frank, Neil Davey, S. Field, 1996 .

The application of Gaussian processes in the prediction of absorption across mammalian skin and synthetic membranes

N. Davey, Yi Sun, G. Moss, 2010 .

The application of discriminant analysis and Machine Learning methods as tools to identify and classify compounds with potential as transdermal enhancers.

G P Moss, A J Shah, R G Adams, 2012, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

Using the Support Vector Machine as a Classification Method for Software Defect Prediction with Static Code Metrics

Bruce Christianson, Neil Davey, Yi Sun, 2009, EANN.

Using Real-Valued Meta Classifiers to Integrate and Contextualize Binding Site Predictions

Neil Davey, Mark Robinson, Yi Sun, 2007, ICANNGA.

Using Feature Selection Filtering Methods for Binding Site Predictions

Neil Davey, Mark Robinson, Yi Sun, 2006, 2006 5th IEEE International Conference on Cognitive Informatics.

Identifying word boundaries in handwrittem text

Alexander V. Shafarenko, Neil Davey, Yi Sun, 2004, 2004 International Conference on Machine Learning and Applications, 2004. Proceedings..

Segmenting handwritten text using supervised classification techniques

Yi Sun, N. Davey, R. Adams, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Word segmentation of handwritten text using supervised classification techniques

Alexander V. Shafarenko, Neil Davey, Yi Sun, 2007, Appl. Soft Comput..

Traffic trends analysis using neural networks

Neil Davey, T. Edwards, Ray J. Frank, 1997 .

Learning through experience: an emergent connectionist account of letter production behaviour

N. Davey, J. Done, R. Adams, 2006, Connection science.

Connectionist models investigating representations formed in the sequential generation of characters

Neil Davey, Fiona M. Richardson, S. H. Anthony, 2002, ESANN.

How the constraints on English compound production might be learnt from the linguistic input : evidence from 4 connectionist models

Neil Davey, Victoria A. Murphy, Pamela Smith, 2003 .

The application of feature selection to the development of Gaussian process models for percutaneous absorption

Neil Davey, Yi Sun, Rod Adams, 2010, The Journal of pharmacy and pharmacology.

Evolution of Dendritic Morphologies Using Deterministic and Nondeterministic Genotype to Phenotype Mapping

Neil Davey, Rod Adams, Parimala Alva, 2013, ICANN.

High Performance Associative Memories and Structured Weight Dilution

Neil Davey, S. Hunt, S. P. Turvey, 2004 .

Non-random weight dilution in high performance associative memories

Neil Davey, S. Hunt, S. P. Turvey, 2002 .

High Performance Associative Memory and Weight Dilution

N. Davey, S. P. Hunt, R. Adams, 2001 .

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Vito Paolo Pastore, Alfred B. Yu, Kelvin S. Oie, 2017, BMC Neuroscience.

The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability

Neil Davey, Yi Sun, Parivash Ashrafi, 2019, The Journal of pharmacy and pharmacology.

Time Series Analysis using Embedding Dimension on Heart Rate Variability

Neil Davey, Yi Sun, Na Helian, 2018, BICA.

Stochasticity applied to a neural tree classifier

Neil Davey, Roger Adams, W. Pensuwon, 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

Comparative performances of stochastic competitive evolutionary neural tree (SCENT) with neural classifiers

Neil Davey, Roger Adams, W. Pensuwon, 2001 .

The importance of hyperparameters selection within small datasets

Neil Davey, Marc B. Brown, Yi Sun, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

The application of machine learning to the modelling of percutaneous absorption: An overview and guide

G P Moss, N Davey, S C Wilkinson, 2015, SAR and QSAR in environmental research.

The application of Gaussian processes in the predictions of permeability across mammalian and polydimethylsiloxane membranes

Neil Davey, Marc B. Brown, Yi Sun, 2012, Artif. Intell. Res..

Feature Selection Modelling for Percutaneous Absorption across Synthetic Membranes

Neil Davey, Yi Sun, Rod Adams, 2014, 2014 IEEE 26th International Conference on Tools with Artificial Intelligence.

The application of stochastic machine learning methods in the prediction of skin penetration

Neil Davey, Marc B. Brown, Yi Sun, 2011, Appl. Soft Comput..

Prediction of Skin Penetration Using Machine Learning Methods

Neil Davey, Marc B. Brown, Yi Sun, 2008, 2008 Eighth IEEE International Conference on Data Mining.