Mark A. Girolami

151 papers A* 13A 7B 5C 3Misc 3Journal 91Unranked 24

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents. CoRR Alessandro Barp, Lancelot Da Costa, Guilherme França, Karl J. Friston, Mark A. Girolami, Michael I. Jordan, Grigorios A. Pavliotis
2020	J	`jnl`	Convergence Guarantees for Gaussian Process Approximations Under Several Observation Models. CoRR George Wynne, François-Xavier Briol, Mark A. Girolami
2019	J	`jnl`	Bayesian Probabilistic Numerical Methods. SIAM Rev. Jon Cockayne, Chris J. Oates, Timothy John Sullivan, Mark A. Girolami
2019	J	`jnl`	Editorial: special edition on probabilistic numerics. Stat. Comput. Mark A. Girolami, Ilse C. F. Ipsen, Chris J. Oates, Art B. Owen, Timothy John Sullivan
2019	J	`jnl`	Embedded Ridge Approximations: Constructing Ridge Approximations Over Localized Scalar Fields For Improved Simulation-Centric Dimension Reduction. CoRR Chun Yui Wong, Pranay Seshadri, Geoffrey T. Parks, Mark A. Girolami
2019	A*	`conf`	Minimum Stein Discrepancy Estimators. NeurIPS Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey
2019	J	`jnl`	Minimum Stein Discrepancy Estimators. CoRR Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey
2019	A*	`conf`	Multi-resolution Multi-task Gaussian Processes. NeurIPS Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami
2019	J	`jnl`	Multi-resolution Multi-task Gaussian Processes. CoRR Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami
2019	A*	`conf`	Precision-Recall Balanced Topic Modelling. NeurIPS Seppo Virtanen, Mark A. Girolami
2019	J	`jnl`	Statistical Inference for Generative Models with Maximum Mean Discrepancy. CoRR François-Xavier Briol, Alessandro Barp, Andrew B. Duncan, Mark A. Girolami
2019	A*	`conf`	Stein Point Markov Chain Monte Carlo. ICML Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark A. Girolami, Lester W. Mackey, Chris J. Oates
2019	J	`jnl`	The synthesis of data from instrumented structures and physics-based models via Gaussian processes. J. Comput. Phys. Alastair Gregory, F. Din-Houn Lau, Mark A. Girolami, Liam J. Butler, Mohammed Z. E. B. Elshafie
2018	J	`jnl`	A Bayesian Conjugate Gradient Method. CoRR Jon Cockayne, Chris J. Oates, Mark A. Girolami
2018	J	`jnl`	Bat detective - Deep learning tools for bat acoustic signal detection. PLoS Comput. Biol. Oisin Mac Aodha, Rory Gibb, Kate E. Barlow, Ella Browning, Michael Firman, Robin Freeman, Briana Harder, Libby Kinsey, Gary R. Mead, Stuart E. Newson, Ivan Pandourski, Stuart Parsons, Jon Russ, Abigel Szodoray-Paradi, Farkas Szodoray-Paradi, Elena Tilova, Mark A. Girolami, Gabriel J. Brostow, Kate E. Jones
2018	A*	`conf`	Bayesian Quadrature for Multiple Related Integrals. ICML Xiaoyue Xi, François-Xavier Briol, Mark A. Girolami
2018	J	`jnl`	Bayesian Quadrature for Multiple Related Integrals. CoRR Xiaoyue Xi, François-Xavier Briol, Mark A. Girolami
2018	J	`jnl`	Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. CoRR Richard Scalzo, David Kohn, Hugo K. H. Olierook, Gregory Houseman, Rohitash Chandra, Mark A. Girolami, Sally Cripps
2018	J	`jnl`	How Deep Are Deep Gaussian Processes? J. Mach. Learn. Res. Matthew M. Dunlop, Mark A. Girolami, Andrew M. Stuart, Aretha L. Teckentrup
2018	J	`jnl`	Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?". CoRR François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic
2017	J	`jnl`	Bayesian Probabilistic Numerical Methods. CoRR Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami
2017	J	`jnl`	Geometric MCMC for infinite-dimensional inverse problems. J. Comput. Phys. Alexandros Beskos, Mark A. Girolami, Shiwei Lan, Patrick E. Farrell, Andrew M. Stuart
2017	J	`jnl`	Geometry and Dynamics for Markov Chain Monte Carlo. CoRR Alessandro Barp, François-Xavier Briol, Anthony D. Kennedy, Mark A. Girolami
2017	A*	`conf`	On the Sampling Problem for Kernel Quadrature. ICML François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark A. Girolami
2017	J	`jnl`	On the Sampling Problem for Kernel Quadrature. CoRR François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark A. Girolami
2017	—	`conf`	Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models. NIPS Chris J. Oates, Steven A. Niederer, Angela W. C. Lee, François-Xavier Briol, Mark A. Girolami
2017	J	`jnl`	Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems. CoRR Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami
2017	J	`jnl`	Statistical analysis of differential equations: introducing probability measures on numerical solutions. Stat. Comput. Patrick R. Conrad, Mark A. Girolami, Simo Särkkä, Andrew M. Stuart, Konstantinos Zygalakis
2016	J	`jnl`	A Bayesian approach to multiscale inverse problems with on-the-fly scale determination. J. Comput. Phys. Louis Ellam, Nicholas Zabaras, Mark A. Girolami
2016	A	`conf`	Control Functionals for Quasi-Monte Carlo Integration. AISTATS Chris J. Oates, Mark A. Girolami
2016	J	`jnl`	Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems. J. Comput. Phys. Shiwei Lan, Tan Bui-Thanh, Mike Christie, Mark A. Girolami
2016	J	`jnl`	Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems. CoRR Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami
2015	—	`conf`	Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. NIPS François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne
2015	A*	`conf`	Ordinal Mixed Membership Models. ICML Seppo Virtanen, Mark A. Girolami
2015	J	`jnl`	Probabilistic Integration. CoRR François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic
2015	J	`jnl`	Probabilistic Numerics and Uncertainty in Computations. CoRR Philipp Hennig, Michael A. Osborne, Mark A. Girolami
2015	J	`jnl`	Unbiased Bayes for Big Data: Paths of Partial Posteriors. CoRR Heiko Strathmann, Dino Sejdinovic, Mark A. Girolami
2014	A	`conf`	Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel. AISTATS Vassilios Stathopoulos, Veronica Zamora-Gutierrez, Kate E. Jones, Mark A. Girolami
2014	J	`jnl`	Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions. Entropy Samuel Livingstone, Mark A. Girolami
2014	—	`conf`	Probabilistic Model Checking of DTMC Models of User Activity Patterns. QEST Oana Andrei, Muffy Calder, Matthew Higgs, Mark A. Girolami
2014	J	`jnl`	Probabilistic Model Checking of DTMC Models of User Activity Patterns. CoRR Oana Andrei, Muffy Calder, Matthew Higgs, Mark A. Girolami
2014	J	`jnl`	Pseudo-Marginal Bayesian Inference for Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. Maurizio Filippone, Mark A. Girolami
2014	B	`conf`	Putting the Scientist in the Loop - Accelerating Scientific Progress with Interactive Machine Learning. ICPR Oisin Mac Aodha, Vassilios Stathopoulos, Gabriel J. Brostow, Michael Terry, Mark A. Girolami, Kate E. Jones
2014	J	`jnl`	mcmc_clib-an advanced MCMC sampling package for ode models. Bioinform. Andrei Kramer, Vassilios Stathopoulos, Mark A. Girolami, Nicole Radde
2013	J	`jnl`	A comparative evaluation of stochastic-based inference methods for Gaussian process models. Mach. Learn. Maurizio Filippone, Mingjun Zhong, Mark A. Girolami
2013	—	`conf`	Analysing user behaviour through dynamic population models. CHI Extended Abstracts Matthew Higgs, Alistair Morrison, Mark A. Girolami, Matthew Chalmers
2013	J	`jnl`	Exact-Approximate Bayesian Inference for Gaussian Processes. CoRR Maurizio Filippone, Mark A. Girolami
2013	J	`jnl`	Online Learning with (Multiple) Kernels: A Review. Neural Comput. Tom Diethe, Mark A. Girolami
2012	J	`jnl`	A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices CoRR Mingjun Zhong, Mark A. Girolami
2012	A*	`conf`	A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. ICML Mingjun Zhong, Mark A. Girolami
2012	J	`jnl`	Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations. Neural Comput. Ke Yuan, Mark A. Girolami, Mahesan Niranjan
2012	A	`conf`	Preface. AISTATS Neil D. Lawrence, Mark A. Girolami
2012	A	`ed.`	Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2012, La Palma, Canary Islands, Spain, April 21-23, 2012 AISTATS Neil D. Lawrence, Mark A. Girolami
2011	—	`book`	A First Course in Machine Learning. Simon Rogers, Mark A. Girolami
2011	—	`ed.`	Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I ICANN (1) Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski
2011	—	`ed.`	Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II ICANN (2) Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski
2011	J	`jnl`	Discussion of the paper: "Sampling schemes for generalized linear Dirichlet process random effects models" by M. Kyung, J. Gill, and G. Casella. Stat. Methods Appl. Maurizio Filippone, Antonietta Mira, Mark A. Girolami
2011	—	`conf`	ITFoM - The IT Future of Medicine. FET Hans Lehrach, Ralf Sudbrak, Peter Boyle, Markus Pasterk, Kurt Zatloukal, Heimo Müller, Tim Hubbard, Angela Brand, Mark A. Girolami, Daniel Jameson, Frank J. Bruggeman, Hans V. Westerhoff
2011	Misc	`conf`	On the Use of Diagonal and Class-Dependent Weighted Distances for the Probabilistic k-Nearest Neighbor. IbPRIA Roberto Paredes, Mark A. Girolami
2011	J	`jnl`	Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation. Int. J. Data Min. Bioinform. Tamara Polajnar, Simon Rogers, Mark A. Girolami
2011	J	`jnl`	Protein interaction sentence detection using multiple semantic kernels. J. Biomed. Semant. Tamara Polajnar, Theodoros Damoulas, Mark A. Girolami
2010	J	`jnl`	Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers. BMC Bioinform. Mohammed Dakna, Keith Harris, Alexandros Kalousis, Sebastien Carpentier, Walter Kolch, Joost P. Schanstra, Marion Haubitz, Antonia Vlahou, Harald Mischak, Mark A. Girolami
2010	J	`jnl`	Infinite factorization of multiple non-parametric views. Mach. Learn. Simon Rogers, Arto Klami, Janne Sinkkonen, Mark A. Girolami, Samuel Kaski
2010	—	`book`	Learning and Inference in Computational Systems Biology. Neil D. Lawrence, Mark A. Girolami, Magnus Rattray, Guido Sanguinetti
2010	J	`jnl`	Multiclass relevance vector machines: sparsity and accuracy. IEEE Trans. Neural Networks Ioannis Psorakis, Theodoros Damoulas, Mark A. Girolami
2010	J	`jnl`	Semi-parametric analysis of multi-rater data. Stat. Comput. Simon Rogers, Mark A. Girolami, Tamara Polajnar
2009	—	`conf`	Analysis of SVM with Indefinite Kernels. NIPS Yiming Ying, Colin Campbell, Mark A. Girolami
2009	—	`conf`	Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami
2009	—	`conf`	Classification of Protein Interaction Sentences via Gaussian Processes. PRIB Tamara Polajnar, Simon Rogers, Mark A. Girolami
2009	J	`jnl`	Combining feature spaces for classification. Pattern Recognit. Theodoros Damoulas, Mark A. Girolami
2009	—	`conf`	Definition of Valid Proteomic Biomarkers: A Bayesian Solution. PRIB Keith Harris, Mark A. Girolami, Harald Mischak
2009	J	`jnl`	Estimating Bayes factors via thermodynamic integration and population MCMC. Comput. Stat. Data Anal. Ben Calderhead, Mark A. Girolami
2009	—	`conf`	Inferring Meta-covariates in Classification. PRIB Keith Harris, Lisa McMillan, Mark A. Girolami
2009	—	`ed.`	Pattern Recognition in Bioinformatics, 4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009. Proceedings PRIB Visakan Kadirkamanathan, Guido Sanguinetti, Mark A. Girolami, Mahesan Niranjan, Josselin Noirel
2009	J	`jnl`	Pattern recognition with a Bayesian kernel combination machine. Pattern Recognit. Lett. Theodoros Damoulas, Mark A. Girolami
2009	J	`jnl`	Probabilistic assignment of formulas to mass peaks in metabolomics experiments. Bioinform. Simon Rogers, Richard A. Scheltema, Mark A. Girolami, Rainer Breitling
2009	A	`conf`	Reversible Jump MCMC for Non-Negative Matrix Factorization. AISTATS Mingjun Zhong, Mark A. Girolami
2009	—	`conf`	Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics. PRIB Tamara Polajnar, Mark A. Girolami
2009	—	`conf`	Using Higher-Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana. PRIB Rónán Daly, Kieron D. Edwards, John S. O'Neill, J. Stuart Aitken, Andrew J. Millar, Mark A. Girolami
2008	—	`conf`	Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes. NIPS Ben Calderhead, Mark A. Girolami, Neil D. Lawrence
2008	J	`jnl`	Bayesian inference for differential equations. Theor. Comput. Sci. Mark A. Girolami
2008	J	`jnl`	Bayesian ranking of biochemical system models. Bioinform. Vladislav Vyshemirsky, Mark A. Girolami
2008	J	`jnl`	Bayesian ranking of biochemical system models. Bioinform. Vladislav Vyshemirsky, Mark A. Girolami
2008	J	`jnl`	BioBayes: A software package for Bayesian inference in systems biology. Bioinform. Vladislav Vyshemirsky, Mark A. Girolami
2008	J	`jnl`	Classifying EEG for brain computer interfaces using Gaussian processes. Pattern Recognit. Lett. Mingjun Zhong, Fabien Lotte, Mark A. Girolami, Anatole Lécuyer
2008	C	`conf`	Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. ICMLA Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell
2008	J	`jnl`	Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models. Bioinform. Simon Rogers, Mark A. Girolami, Walter Kolch, Katrina M. Waters, Tao Liu, Brian Thrall, H. Steven Wiley
2008	J	`jnl`	ParCrys: a Parzen window density estimation approach to protein crystallization propensity prediction. Bioinform. Ian M. Overton, Gianandrea Padovani, Mark A. Girolami, Geoffrey J. Barton
2008	J	`jnl`	Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection. Bioinform. Theodoros Damoulas, Mark A. Girolami
2008	J	`jnl`	vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R. Bioinform. Nicola Lama, Mark A. Girolami
2007	J	`jnl`	An empirical analysis of the probabilistic K-nearest neighbour classifier. Pattern Recognit. Lett. S. Manocha, Mark A. Girolami
2007	J	`jnl`	Bayesian model-based inference of transcription factor activity. BMC Bioinform. Simon Rogers, Raya Khanin, Mark A. Girolami
2007	A	`conf`	Detecting worm variants using machine learning. CoNEXT Oliver Sharma, Mark A. Girolami, Joseph S. Sventek
2007	J	`jnl`	Employing Latent Dirichlet Allocation for fraud detection in telecommunications. Pattern Recognit. Lett. Dongshan Xing, Mark A. Girolami
2007	—	`conf`	Multi-class Semi-supervised Learning with the e-truncated Multinomial Probit Gaussian Process. Gaussian Processes in Practice Simon Rogers, Mark A. Girolami
2006	J	`jnl`	Clustering via kernel decomposition. IEEE Trans. Neural Networks Anna Szymkowiak-Have, Mark A. Girolami, Jan Larsen
2006	—	`conf`	Data Integration for Classification Problems Employing Gaussian Process Priors. NIPS Mark A. Girolami, Mingjun Zhong
2006	—	`conf`	Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm. NIPS Robert Jenssen, Torbjørn Eltoft, Mark A. Girolami, Deniz Erdogmus
2006	—	`conf`	Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation. NIPS Gavin C. Cawley, Nicola L. C. Talbot, Mark A. Girolami
2006	J	`jnl`	Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. Neural Comput. Mark A. Girolami, Simon Rogers
2005	J	`jnl`	A Bayesian regression approach to the inference of regulatory networks from gene expression data. Bioinform. Simon Rogers, Mark A. Girolami
2005	—	`conf`	Disease Classification from Capillary Electrophoresis: Mass Spectrometry. ICAPR (1) Simon Rogers, Mark A. Girolami, Ronald Krebs, Harald Mischak
2005	A*	`conf`	Hierarchic Bayesian models for kernel learning. ICML Mark A. Girolami, Simon Rogers
2005	A*	`conf`	Probabilistic hyperspace analogue to language. SIGIR Leif Azzopardi, Mark A. Girolami, Malcolm K. Crowe
2005	J	`jnl`	Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains. Data Min. Knowl. Discov. Mark A. Girolami, Ata Kabán
2005	J	`jnl`	The Latent Process Decomposition of cDNA Microarray Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. Simon Rogers, Mark A. Girolami, Colin Campbell, Rainer Breitling
2004	C	`conf`	An Assessment of Feature Relevance in Predicting Protein Function from Sequence. IDEAL Ali Al-Shahib, Chao He, Aik Choon Tan, Mark A. Girolami, David R. Gilbert
2004	J	`jnl`	Biologically valid linear factor models of gene expression. Bioinform. Mark A. Girolami, Rainer Breitling
2004	J	`jnl`	Employing optimized combinations of one-class classifiers for automated currency validation. Pattern Recognit. Chao He, Mark A. Girolami, Gary Ross
2004	J	`jnl`	Novelty detection employing an L2 optimal non-parametric density estimator. Pattern Recognit. Lett. Chao He, Mark A. Girolami
2004	A*	`conf`	User biased document language modelling. SIGIR Leif Azzopardi, Mark A. Girolami, Cornelis Joost van Rijsbergen
2003	A*	`conf`	Investigating the relationship between language model perplexity and IR precision-recall measures. SIGIR Leif Azzopardi, Mark A. Girolami, Keith van Rijsbergen
2003	A*	`conf`	On an equivalence between PLSI and LDA. SIGIR Mark A. Girolami, Ata Kabán
2003	J	`jnl`	Probability Density Estimation from Optimally Condensed Data Samples. IEEE Trans. Pattern Anal. Mach. Intell. Mark A. Girolami, Chao He
2003	—	`conf`	Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles. NIPS Mark A. Girolami, Ata Kabán
2003	J	`jnl`	Topic Identification in Dynamical Text by Complexity Pursuit. Neural Process. Lett. Ella Bingham, Ata Kabán, Mark A. Girolami
2002	J	`jnl`	A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams. J. Intell. Inf. Syst. Ata Kabán, Mark A. Girolami
2002	C	`conf`	A General Framework for a Principled Hierarchical Visualization of Multivariate Data. IDEAL Ata Kabán, Peter Tiño, Mark A. Girolami
2002	J	`jnl`	A Probabilistic Framework for the Hierarchic Organisation and Classification of Document Collections. J. Intell. Inf. Syst. Alexei Vinokourov, Mark A. Girolami
2002	A	`ed.`	Advances in Information Retrieval, 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25-27, 2002 Proceedings ECIR Fabio Crestani, Mark A. Girolami, C. J. van Rijsbergen
2002	J	`jnl`	Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus. Neural Process. Lett. Ata Kabán, Mark A. Girolami
2002	J	`jnl`	Latent variable models for the topographic organisation of discrete and strictly positive data. Neurocomputing Mark A. Girolami
2002	J	`jnl`	Mercer kernel-based clustering in feature space. IEEE Trans. Neural Networks Mark A. Girolami
2002	J	`jnl`	Orthogonal Series Density Estimation and the Kernel Eigenvalue Problem. Neural Comput. Mark A. Girolami
2002	J	`jnl`	Report on the 24th European Colloquium on Information Retrieval Research. SIGMOD Rec. Fabio Crestani, Mark A. Girolami
2002	J	`jnl`	Report on the 24th European colloquium on information retrieval research (ECIR 2002). SIGIR Forum Fabio Crestani, Mark A. Girolami, C. J. van Rijsbergen
2001	J	`jnl`	A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data. IEEE Trans. Pattern Anal. Mach. Intell. Ata Kabán, Mark A. Girolami
2001	J	`jnl`	A Variational Method for Learning Sparse and Overcomplete Representations. Neural Comput. Mark A. Girolami
2001	J	`jnl`	An Expectation-Maximization Approach to Nonlinear Component Analysis. Neural Comput. Roman Rosipal, Mark A. Girolami
2001	—	`conf`	Finding Topics in Dynamical Text: Application to Chat Line Discussions. WWW Posters Ella Bingham, Ata Kabán, Mark A. Girolami
2001	J	`jnl`	Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression. Neural Comput. Appl. Roman Rosipal, Mark A. Girolami, Leonard J. Trejo, Andrzej Cichocki
2001	J	`jnl`	The topographic organization and visualization of binary data using multivariate-Bernoulli latent variable models. IEEE Trans. Neural Networks Mark A. Girolami
2000	B	`conf`	A generative model for sparse discrete binary data with non-uniform categorical priors. ESANN Mark A. Girolami
2000	—	`conf`	Extraction of Sleep-Spindles from the Electroencephalogram (EEG). ANNIMAB Allan Kardec Barros, Roman Rosipal, Mark A. Girolami, Georg Dorffner, Noboru Ohnishi
2000	B	`conf`	Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents. ICPR Ata Kabán, Mark A. Girolami
2000	—	`conf`	Kernel PCA Feature Extraction of Event-Related Potentials for Human Signal Detection Performance. ANNIMAB Roman Rosipal, Mark A. Girolami, Leonard J. Trejo
2000	B	`conf`	Probabilistic Hierarchical Clustering Method for Organizing Collections of Text Documents. ICPR Alexei Vinokourov, Mark A. Girolami
2000	—	`conf`	The Organization and Visualization of Document Corpora: A Probabilistic Approach. DEXA Workshop Mark A. Girolami, Alexei Vinokourov, Ata Kabán
1999	J	`jnl`	Blind source separation of more sources than mixtures using overcomplete representations. IEEE Signal Process. Lett. Te-Won Lee, Michael S. Lewicki, Mark A. Girolami, Terrence J. Sejnowski
1999	J	`jnl`	Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources. Neural Comput. Te-Won Lee, Mark A. Girolami, Terrence J. Sejnowski
1998	J	`jnl`	A common neural-network model for unsupervised exploratory data analysis and independent component analysis. IEEE Trans. Neural Networks Mark A. Girolami, Andrzej Cichocki, Shun-ichi Amari
1998	J	`jnl`	A nonlinear model of the binaural cocktail party effect. Neurocomputing Mark A. Girolami
1998	J	`jnl`	An Alternative Perspective on Adaptive Independent Component Analysis Algorithms. Neural Comput. Mark A. Girolami
1998	Misc	`conf`	Noise reduction and speech enhancement via temporal anti-Hebbian learning. ICASSP Mark A. Girolami
1998	J	`jnl`	The Latent Variable Data Model for Exploratory Data Analysis and Visualisation: A Generalisation of the Nonlinear Infomax Algorithm. Neural Process. Lett. Mark A. Girolami
1997	J	`jnl`	An extended exploratory projection pursuit network with linear and nonlinear anti-hebbian lateral connections applied to the cocktail party problem. Neural Networks Mark A. Girolami, Colin Fyfe
1997	—	`conf`	Generalised independent component analysis through unsupervised learning with emergent Bussgang properties. ICNN Mark A. Girolami, Colin Fyfe
1997	B	`conf`	Independence is far from normal. ESANN Mark A. Girolami, Colin Fyfe
1997	Misc	`conf`	Kurtosis extrema and identification of independent components: a neural network approach. ICASSP Mark A. Girolami, Colin Fyfe
1997	J	`jnl`	Stochastic ICA Contrast Maximisation Using Oja's Nonlinear PCA Algorithm. Int. J. Neural Syst. Mark A. Girolami, Colin Fyfe
1996	J	`jnl`	A Temporal Model of Linear Anti-Hebbian Learning. Neural Process. Lett. Mark A. Girolami, Colin Fyfe