UNIVERSITY of GLASGOW

Computing at Glasgow University
 

Publications for 'Inference Group Collection' ordered by Year. (107)

2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1994

2012

On the Fully Bayesian Treatment of Latent Gaussian Models using Stochastic Simulations
Filippone,M. Zhong,M. Girolami,M. DCS Technical Report Series pp 36 Dept of Computing Science, University of Glasgow [More Details].

2011

Learning Bayesian Networks: Approaches and Issues
Daly,R. Shen,Q. Aitken,S. The Knowledge Engineering Review pp 99-157 Cambridge University Press [More Details].

2010

Analysis of SVM with Indefinite Kernels
Ying,Y. Campbell,C.
Girolami,M. NIPS 2009 MIT Press [More Details].

HexServer: an FFT-based protein docking server powered by graphics processors
MACINDOE,G. MAVRIDIS,L. VENKATRAMAN,V. DEVIGNES,M. RITCHIE,D.W. Nucleic Acids Research Oxford University Press [More Details].

Predictive response-relevant clustering of expression data provides insights into disease processes
Hopcroft,L.E. McBride,M.W. Harris,K. Sampson,A.K. McClure,J.D. Graham,D. Young,G. Holyoake,T.L. Girolami,M.A. Dominiczak,A.F. Nucleic Acids Research [More Details].

Protein Interaction Detection in Sentences via Gaussian Processes: A preliminary evaluation
Polajnar,T. Rogers,S. Girolami,M. International Journal of Data Mining and Bioinformatics [More Details].

2009

Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
Calderhead,B. Girolami,M. Lawrence,N. Advances in Neural Information Processing Systems 21 (2009) pp 217-224 MIT Press [More Details].

Bayesian Methods to Detect Dye Labelled DNA Oligonucleotides in Multiplexed Raman Spectra
Zhong,M. Girolami,M. Faulds,K. Graham,D. pp 20 [More Details].

Class Prediction from Disparate Biological Data Sources using an Iterative Multi-kernel Algorithm
Ying,Y. Campbell,C. Damoulas,T. Girolami,M.A. Lecture Notes in Bioinformatics, Proceedings of the 4th IAPR International Conference, Pattern Recognition in Bioinformatics 2009 (PRIB 2009) pp 427-438 Springer Verlag [More Details].

Classification of Protein Interaction Sentences via Gaussian Processes
Polajnar,T. Rogers,S. Girolami,M. Lecture Notes in Bioinformatics, Proceedings of 4th IAPR International Conference, Pattern Recognition in Bioinformatics 2009 pp 282–292 Springer Verlag [More Details].

Combining Feature Spaces for Classification
Damoulas,T. Girolami,M.A. Pattern Recognition, Volume 42, Issue 11 pp 2671-2683 Elsevier Science [More Details].

Definition of Valid Proteomic Biomarkers: A Bayesian Solution
Harris,K. Girolami,M. Mischak,H. Pattern Recognition In Bioinformatics 2009 Springer Verlag [More Details].

Estimating Bayes Factors via Thermodynamic Integration and Population MCMC
Calderhead,B. Girolami,M. Computational Statistics and Data Analysis 53 (2009). DOI information: 10.1016/j.csda.2009.07.025 pp 4028-4045 Elsevier Science [More Details].

Inferring Meta-covariates in Classification
Harris,K. Hopcroft,L.E. Girolami,M. Pattern Recognition In Bioinformatics 2009 Springer Verlag [More Details].

Learning Bayesian Network Equivalence Classes with Ant Colony Optimization
Daly,R. Shen,Q. Journal of Artificial Intelligence Research pp 391--447 AAAI Press [More Details].

Probabilistic assignment of formulas to mass peaks in metabolomics experiments
Rogers,S. Scheltema,R. Girolami,M.A. Breitling,R. Bioinformatics, 25(4) pp 512--518 Oxford University Press [More Details].

Reversible Jump MCMC for Non-Negative Matrix Factorization
Zhong,M. Girolami,M. In D. Dyk and M. Welling, editors, Proceedings of the 12th International Conference on Artificial Intelligence and Statistics, volume 5, pages 663-670, 2009 pp 8 [More Details].

Riemannian Manifold Hamiltonian Monte Carlo
Girolami,M. Calderhead,B. Chin,S. DCS Technical Report Series pp 35 Dept of Computing Science, University of Glasgow [More Details].

Semi-Parametric Analysis of Multi-Rater Data
Rogers,S. Girolami,M. Polajnar,T. Statistics and Computing Springer [More Details].

Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics
Polajnar,T. Girolami,M. Lecture Notes in Bioinformatics, Proceedings of the 4th IAPR International Conference, Pattern Recognition in Bioinformatics 2009 pp 270–281 Springer Verlag [More Details].

Using Higher-Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana
Daly,R. Edwards,K.D. O'Neill,J.S. Aitken,S. Millar,A.J. Girolami,M. Proceedings of the Fourth IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009) pp 67--78 LNCS, Springer [More Details].

2008

Bayesian Inference for Differential Equations
Girolami,M. Theoretical Computer Science Elsevier Science [More Details].

Bayesian Ranking of Biochemical System Models
Vyshemirsky,V. Girolami,M. Bioinformatics Oxford University Press [More Details].

BioBayes: A Software Package for Bayesian Inference in Systems Biology
Vyshemirsky,V. Girolami,M. Bioinformatics Oxford University Press [More Details].

BRCA1 and BRCA2 Missense Variants of High and Low Clinical Significance Influence Lymphoblastoid Cell Line Post-Irradiation Gene Expression
Waddell,N. Ten Haaf,A. Marsh,A. Johnson,J. Walker,L. Gongora,M. Brown,M. Grover,P. Girolami,M. Grimmond,S. Chenevix-Trench,G. Spurdle,A. PLoS Genetics pp e1000080 [More Details].

Classifying EEG for Brain Computer Interfaces Using Gaussian Processes
Zhong,M. Lotte,F. Girolami,M. Lecuyer,A. Pattern Recognition Letters [More Details].

Inference in a Gene Regulatory Network with Transcriptional Time Delay
Higham,C.F. DCS Technical Report Series Dept of Computing Science, University of Glasgow [More Details].

Inferring Sparse Kernel Combinations and Relevance Vectors: An application to subcellular localization of proteins
Damoulas,T. Ying,Y. Girolami,M. Campbell,C. International Conference on Machine Learning and Applications, IEEE [More Details].

Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models
Rogers,S.D. Girolami,M.A. Kolch,W. Waters,K.M. Liu,T. Thrall,B. Wiley,H.S. Bioinformatics, Volume 24, Number 24 pp pages 2894–2900 Oxford University Press [More Details].

ParCrys: A Parzen Window Density Estimation Approach to Protein Crystallisation Propensity Prediction
Overton,I. Padovani,G. Girolami,M. Barton,G. Bioinformatics Oxford University Press [More Details].

Pattern recognition with a Bayesian kernel combination machine
Damoulas,T. Girolami,M. Pattern Recognition Letters, Volume 30, Issue 1, Elsevier Science [More Details].

Probabilistic multi-class multi-kernel learning: On protein fold recognition and remote homology detection
Damoulas,T. Girolami,M. Bioinformatics, 24(10) pp 1264-70 Oxford University Press [More Details].

Sloppy Parameters in Oscillatory Systems with Unobserved Species
Calderhead,B. Girolami,M. Proceedings of the Fifth International Workshop on Computational Systems Biology pp 21-24 [More Details].

vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R
Lama,N. Girolami,M. Bioinformatics Oxford University Press [More Details].

2007

An empirical analysis of the probabilistic k-nearest neighbour classifier
Manocha,S.
Girolami,M. Pattern Recognition Letters, Volume 28, Number 13 pp 1818-1824 Elsevier Science [More Details].

Bayesian model-based inference of transcription factor activity
Rogers,S. Khanin,R. Girolami,M. BMC Bioinformatics pp 8 Suppl 2:S2 [More Details].

Data Integration for Classification Problems Employing Gaussian Process Priors
Girolami,M. Zhong,M. Twentieth Annual Conference on Neural Information Processing Systems - NIPS 2006 MIT Press [More Details].

Detecting Worm Variants using Machine Learning
Sharma,O. Girolami,M. Sventek,J.S. Proceedings of the 3rd International Conference on emerging Networking EXperiments and Technologies (CoNEXT), New York, NY, USA, December 2007 ACM [More Details].

Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm
Jensen,R. Eltoft,T. Girolami,M. Erdogmus,D. Twentieth Annual Conference on Neural Information Processing Systems - NIPS 2006 MIT Press [More Details].

Multi-class semi-supervised learning with the e-truncated multinomial probit Gaussian process
Rogers,S. Girolami,M. Proceeding of the Gaussian Processes in Practice Workshop, 2006 [More Details].

Sparse Multinomial Logistic Regression via Bayesian Regularisation using a Laplace Prior
Cawley,G. Talbot,N. Girolami,M. Twentieth Annual Conference on Neural Information Processing Systems - NIPS 2006 MIT Press [More Details].

2006

A Bayesian analysis of the ERK signalling pathway
Vyshemirsky,V. Girolami,M. Gormand,A. Kolch,W. Department of Computing Science Technical Reports pp 1--34 [More Details].

Accurate Prediction of BRCA1 and BRCA2 heterozygous genotype using expression profiling after induced DNA damage
Kote-Jarai,Z. Matthews,L. Osorio,A. Shanley,S. Giddings,I. Moseews,F. Locke,I. Evans,G. Girolami,M. Williams,R. Campbell,C. Clinical Cancer Research, Vol. 12, No. 13, pp. 3896 - 3901 [More Details].

Clustering via Kernel Decomposition
Szymkowiak-Have,A. Girolami,M. Larsen,J. IEEE Transactions on Neural Networks, Vol. 17, No. 1, pp. 256-264 IEEE [More Details].

Identification of Prognostic Signatures in Breast Cancer Microarray Data using Bayesian Techniques
Carrivick,L. Rogers,S. Clark,J. Campbell,C. Girolami,M. Cooper,C. Journal of the Royal Society Interface, Vol.3, No.8. pp 367-381 [More Details].

Query Performance Prediction
He,B. Ounis,I. Information Systems (In press) Elsevier Science [More Details].

Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors
Girolami,M.A. Rogers,S. Neural Computation, Volume 18, Number 8, pages 1790 - 1817. pp 28 MIT Press [More Details].

2005

A Bayesian Regression Approach to the Inference of Regulatory Networks from Gene Expression Data
Rogers,S.
Girolami,M. Bioinformatics, Vol 21, Nos 14, pp 313 - 3137. Oxford University Press [More Details].

Disease Classification with Capillary Electrophoresis:Mass Spectrometry
Rogers,S. Girolami,M. Krebs,R. Mischak,H. International Conference for Advances in Pattern Recognition, Bath 2005 [More Details].

Hierarchic Bayesian Models for Kernel Learning
Girolami,M. Rogers,S. Proceedings of 22nd International Conference on Machine Learning pp 8 [More Details].

Probabilistic Hyperspace Analogue to Language
Azzopardi,L. Girolami,M. Crowe,M. Proceedings of the 28th Annual ACM Conference on Research and Development in Infomration Retrieval (SIGIR 2005) pp 575-576 [More Details].

Sequential Activity Profiling : Latent Dirichlet Allocation of Markov Chains
Girolami,M. Kaban,A. Data Mining and Knowledge Discovery, Vol 10, pp 175 - 196. Kluwer [More Details].

The Latent Process Decomposition of cDNA Microarray Datasets
Rogers,S. Girolami,M. Campbell,C. Breitling,R. IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 2, Number 2. pp 143-156 IEEE Computer Society Press [More Details].

2004

Biologically Valid Linear Factor Models of Gene Expression
Girolami,M. Breitling,R. Bioinformatics, Vol 20, Nos 17, pp 3021 - 3033. pp 26 Oxford University Press [More Details].

Employing Optimised Combinations of One-Class Classifiers for Automated Currency Validation
He,C. Girolami,M. Ross,G. Pattern Recognition Vol 37, Nos 6 pp 1085-1096 Elsevier Science [More Details].

Novelty Detection Employing an L2 Optimal Nonparametric Density Estimator
He,C. Girolami,M. Pattern Recognition Letters, Vol 25, Nos 12, pp 1389-1397. Elsevier Science [More Details].

Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles
Girolami,M. Kaban,A. Advances in Neural Information Processing Systems 16, eds Sebastian Thrun and Lawrence Saul and Bernhard Scholkopf, MIT Press pp 9 - 16 MIT Press [More Details].

Topic Based Language Models for Ad Hoc Information Retrieval
Azzopardi,L. Girolami,M. van Rijsbergen,C.J. Proceedings of the International Joint Conference in Neural Networks (IJCNN 2004) [More Details].

User Biased Document Language Modelling
Azzopardi,L. Girolami,M. van Rijsbergen,C.J. pp 542-544 [More Details].

2003

A Process for Automated Currency Validation
Girolami,M. He,C. Ross,G. [More Details].

Investigating the Relationship between Language Model Perplexity and IR Precision-Recall Measures
Azzopardi,L. Girolami,M. van Rijsbergen,C.J. 26th ACM Conference on Research and Development in Ingormation Retrieval, SIGIR pp 369-370 [More Details].

On an Equivalence between PLSI and LDA
Girolami,M. Kaban,A. 26th ACM Conference on Research and Development in Information Retrieval, SIGIR pp 433-434 [More Details].

Probability Density Estimation from Optimally Condensed Data Samples
Girolami,M. He,C. IEEE Transactions Pattern Analysis and Machine Intelligence pp v.25 no.10 1253-1264 IEEE [More Details].

2002

"Artificial Intelligence Systmes Techniques and Applications in Speech Processing"
Campbell,D.R. Fyfe,C.
Girolami,M. Intelligence Systems Technology and Applications, Vol.III Signal, Image and Speech processing, 1-48, Ed: C T Leondes pp V.III 1-48 CRC Press [More Details].

A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams
Kaban,A. Girolami,M. Journal of Intelligent Information Systems pp v,18 no.2&3 107-125 [More Details].

A General Framework for Principled Hierachical Visulisation of Multivariate Data
Kaban,A. Tino,P. Girolami,M. Third International Conference on Intelligent Data Engineering and Automated Learnind (IDEAL`02) pp 518-523 [More Details].

A Probabilistic Framework for the Hierachic Organisation & Classification of Document Collections
Vinokourov,A. Girolami,M. Journal of Intelligent Information Systems pp v.18 No. 2&3, 153-172 [More Details].

Advances in Infomration Retrieval
Crestani,F. Girolami,M. van Rijsbergen,C. 24th BCS-IRSG European Colloquium on IR Research, Glasgow, UK, 2002 Springer Verlag [More Details].

Fast extraction of Semantic features from a Latent Semantic Indexed Text Corpus
Kaban,A. Girolami,M. Neural Processing Letters pp v.15 No.1 [More Details].

Mercer Kernel Based Clustering in Feature Space
Girolami,M. IEEE Transactions on Neural Networks pp v.13, No.4, 780-784 IEEE [More Details].

Orthogonal Series Density Estimation and the Kernel Eigenvalue Problem
Girolami,M. Neural Computation pp v.13 No.4 669-668 MIT Press [More Details].

Protein structural similarities and prediction of protein function
Chakrabarti,S. Bhavana,S. Mallika,V. Sowdhamini,R. Trends in Chemistry [More Details].

Topic Indentification in Chat line Discussions by Extracting Independent Minimum Complexity Time Components.
Bingham,E. Kaban,A. Girolami,M. Neural Processing Letters pp v.17 1-15 [More Details].

2001

`ICA: Principles and Practice'
Girolami,M. Latent Class and Trait Models for Data Classification and Visulisation. Editors Stephen Roberts (Oxford University) & Richard Everson (Exeter University). Cambridge University Press [More Details].

A Combined Latent Class and Trait Model for the Analysis and Visualisation of Discrete Data
Kaban,A. Girolami,M. IEEE Transactions on Pattern Analysis and Machine Intelligence pp v.23, no.8 859-872 IEEE Computer Society Press [More Details].

A Variational Method for Learning Sparse and Overcomplete Representations
Girolami,M. Neural Computation pp v.13, no.11, 2517-2532 MIT Press [More Details].

A Variational Method fro Learning Sparse and Overcomplete Representations
Girolalmi,M. Neural Computation pp v.13 no.11, 2517-2532 MIT Press [More Details].

An Expectation Maximisation Approach to Nonlinear Component Analysis
Rosipal,R. Girolami,M. Neural Computation MIT Press [More Details].

Document classification employing the Fisher kernel derived from probabilistic hierachic corpus representations
Vinolourov,A. Girolami,M. [More Details].

Document classification employing the Fisher kernel derived from probabilistic hierachic corpus representations
Vinolourov,A. Girolami,M. 23rd European Colloquium on IR Research [More Details].

Finding topics in dynamical text: application to chat line discussions
Bingham,E. Kaban,A. Girolami,M. 10th International World Wide Web Conference (WWW10) pp 198-199 [More Details].

Kernel PCA for Feature Extraction and De-Noising in Non-Linear Regression
Rosipal,R. Girolami,M. Trejo,L. Neural Computing and Applications pp v.10, no.3, 231-243 [More Details].

Latent Variable Models for the Topographic Organisation of Discrete and Strictly Positive Data
Girolami,M. Neural Computation pp v.48, no.1-4, 185-198 MIT Press [More Details].

The Topographic Organisation and Visulisation of Binary Data using Mutivariate-Bernoulli Latent Variable Models
Girolami,M. IEEE Transactions on Neural Networks pp v.12, no.6, 1367-1374 IEE Publications [More Details].

2000

A Generative Model for Sparse Discrete Binary Data with Non-Uniform Categorical Priors
Girolami,M. In proceedings of ESANN'00, European Symposium on Artificial Neural Networks pp 1-6 [More Details].

A Unifying Information Theoretic Framework for Independent Component Analysis
Lee,T.W. Girolami,M. Bell,A.J. Sejnowski,T.A. International Journal on Mathematical and Computer Modelling pp no.39 1-21 [More Details].

Clustering of Text Documents by Skewness Maximisation
Kaban,A. Girolami,M. 2'nd International Workshop on Independent Component Analysis and Blind Source Separation, ICA'2000, Helsinki pp 435-440 [More Details].

Extraction of Sleep-Spindles from the Electroencephalogram
Barros,A. Rosipal,R. Girolami,M. Doerfner,G. In proceedings of International Conference on Artificial Neural Networks in Medicine and Biology. Editors Malmgren, Borga and Niklasson pp 125-130 [More Details].

Implementing Decisions in Binary Decision Trees Using Independent Component Analysis
Pajunen,P. Girolami,M. 2'nd International Workshop on Independent Component Analysis and Blind Source Separation, ICA'2000, Helsinki pp 483-488 [More Details].

Kernel PCA Feature Extracton of Event-Related Potentials for Human Signal Detection Performance
Rosipa,R. Girolami,M. Trejo,L. In proceedings of International Conference on Artificial Neural Networks in Medicine Biology. Editors Malmgen, Borga and Niklasson pp 321-326 [More Details].

Perspective in Neural Computation
Girolami,M. Advances in Independent Component Analysis. Editor J.Taylor Springer Verlag [More Details].

The Organisation and Visualisation of Document Corpoar: A Probabilistic Approach
Girolami,M. Vinokourov,A. Kaban,A. Invited paper, DEXA, 2000. 11'th International Conference and Workshop on Database and Expert Systems Applications pp 558-564 [More Details].

1999

Blind Source Separation of More Sources Using Overcomplete Representations
Lee,T.W. Lewicki,M.S.
Girolami,M. Sejnowski,T. IEEE Signal Processing Letters pp v.1, no.4 87-90 IEE [More Details].

Independent Component Analysis using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources
Lee,T.W. Girolami,M. Sejnowski,T. Neural Computation pp v, 11, no.2, 606-633 [More Details].

Self-Organising Neural Networks: Independent Component Analysis and Blind Signal Separation
Girolami,M. Perspectives in Neural Computatation, Editor J.Taylor Springer Verlag [More Details].

Stochastic ICA Contrast Maximisation Using Oja's Nonlinear PCA Algorithm
Girolami,M. Fyfe,C. International Journal of Neural Systems pp v.8, no.5&6, 661-678 [More Details].

1998

A Common Neural Network Model for Exploratory Data Analysis and Independent Component Analysis
Girolami,M. Cichocki,A. Amari,S.I. IEEE Transactions on Neural Networks pp V 9, No.6 1495 -1501 IEEE [More Details].

A Nonlinear Model of the Binaural Cocktail Party Effect
Girolami,M. Neurocomputing pp v.22, No.1-3, 201-205 [More Details].

An Alternative Perspective on Adaptive Independent Component Analysis Algorithms
Girolami,M. Neural Computation pp vol 10, No.8 2103-2114 [More Details].

The Latent Variable Data Model for Expolartory Data Analysis and Visualisation: A Generalisation of the Nonlinear Infomax Algorithm
Girolami,M. Neural Processing Letters pp V.8, No.1, 27-39 [More Details].

1997

Adaptive Processing Schemes Inspired by Binaural Unmasking for Enhancement of Speech Corrupted with Noise and Reverberation
Shields,P.
Girolami,M. Campbell,D. Fyfe,C. Neuromorphic Systems: Engineering Silicon for Neurobiology, Editors L.S.Smith and A.Hamilton pp 61-74 World Scientific [More Details].

An Extended Exploratory Projection Persuit Network with Linear and Nonlinear Anti-Hebbian Connections Applied to the Cocktail Party Problem
Girolami,M. Fyfe,C. Neural Networks pp v.10, No.9, 1607-1618 [More Details].

Evidence for zooid senescence in the marine bryozoan Electra pilosa
Bayer,M.M. Todd,C.D. Invertebrate Biology, vol. 116 pp 331-340 [More Details].

Extraction of Independent Signal Sources using a Deflationary Exploratory Projection Persuit Network with Lateral Inhibition
Girolami,M. Fyfe,C. I.E.E. Proceedings on Vision, Image and Signal Processing pp v.14, no.5, 299-306 [More Details].

Symmetric Adaptive Maximum Likelihood Estimation for Noise Cancellation and Signal Separation
Girolami,M. Electronics Letters pp v.33, No.17, 1437-1438 [More Details].

1996

A Temporal Model of Linear Anti-Hebbian Learning
Girolami,M. Fyfe,C. Neural Processing Letters pp v.4, no.3, 1-10 [More Details].

1994

Genotypic variation of polypide regression, growth rate and colony form in the marine bryozoan Electra pilosa (L.)
Bayer,M.M. MSc thesis, 95 pp. School of Biological and Medical Sciences, University of St Andrews, Scotland [More Details].