
Mark A. Girolami
Mark Girolami
Person information
- affiliation: University of Cambridge, UK
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2020 – today
- 2020
- [j72]Karla Monterrubio-Gómez, Lassi Roininen
, Sara Wade, Theodoros Damoulas, Mark Girolami
:
Posterior inference for sparse hierarchical non-stationary models. Comput. Stat. Data Anal. 148: 106954 (2020) - [c56]Seppo Virtanen, Mark Girolami:
Dynamic content based ranking. AISTATS 2020: 2315-2324 - [i23]George Wynne, François-Xavier Briol, Mark A. Girolami:
Convergence Guarantees for Gaussian Process Approximations Under Several Observation Models. CoRR abs/2001.10818 (2020) - [i22]Toni Karvonen, Chris J. Oates, Mark Girolami:
Integration in reproducing kernel Hilbert spaces of Gaussian kernels. CoRR abs/2004.12654 (2020) - [i21]Rebecca Ward, Ruchi Choudhary, Alastair Gregory, Mark Girolami:
Continuous calibration of a digital twin: comparison of particle filter and Bayesian calibration approaches. CoRR abs/2011.09810 (2020) - [i20]Pranay Seshadri, Andrew B. Duncan, George Thorne, Geoffrey T. Parks, Mark Girolami:
Bayesian Assessments of Aeroengine Performance. CoRR abs/2011.14698 (2020)
2010 – 2019
- 2019
- [j71]Gishan Don Ranasinghe
, Tony Lindgren
, Mark Girolami
, Ajith Kumar Parlikad
:
A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability. IEEE Access 7: 183996-184007 (2019) - [j70]Alastair Gregory, F. Din-Houn Lau
, Mark A. Girolami
, Liam J. Butler, Mohammed Z. E. B. Elshafie:
The synthesis of data from instrumented structures and physics-based models via Gaussian processes. J. Comput. Phys. 392: 248-265 (2019) - [j69]Mark A. Girolami
, Ilse C. F. Ipsen, Chris J. Oates, Art B. Owen, Timothy John Sullivan:
Editorial: special edition on probabilistic numerics. Stat. Comput. 29(6): 1181-1183 (2019) - [j68]Jon Cockayne, Chris J. Oates, Timothy John Sullivan, Mark A. Girolami
:
Bayesian Probabilistic Numerical Methods. SIAM Rev. 61(4): 756-789 (2019) - [c55]Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark A. Girolami, Lester W. Mackey, Chris J. Oates:
Stein Point Markov Chain Monte Carlo. ICML 2019: 1011-1021 - [c54]Seppo Virtanen, Mark A. Girolami:
Precision-Recall Balanced Topic Modelling. NeurIPS 2019: 6747-6756 - [c53]Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey:
Minimum Stein Discrepancy Estimators. NeurIPS 2019: 12964-12976 - [c52]Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami:
Multi-resolution Multi-task Gaussian Processes. NeurIPS 2019: 14025-14035 - [i19]François-Xavier Briol, Alessandro Barp, Andrew B. Duncan, Mark A. Girolami:
Statistical Inference for Generative Models with Maximum Mean Discrepancy. CoRR abs/1906.05944 (2019) - [i18]Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey:
Minimum Stein Discrepancy Estimators. CoRR abs/1906.08283 (2019) - [i17]Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami:
Multi-resolution Multi-task Gaussian Processes. CoRR abs/1906.08344 (2019) - [i16]Chun Yui Wong, Pranay Seshadri, Geoffrey T. Parks, Mark A. Girolami:
Embedded Ridge Approximations: Constructing Ridge Approximations Over Localized Scalar Fields For Improved Simulation-Centric Dimension Reduction. CoRR abs/1907.07037 (2019) - 2018
- [j67]Matthew M. Dunlop, Mark A. Girolami, Andrew M. Stuart, Aretha L. Teckentrup:
How Deep Are Deep Gaussian Processes? J. Mach. Learn. Res. 19: 54:1-54:46 (2018) - [j66]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
:
Bat detective - Deep learning tools for bat acoustic signal detection. PLoS Comput. Biol. 14(3) (2018) - [c51]Xiaoyue Xi, François-Xavier Briol, Mark A. Girolami:
Bayesian Quadrature for Multiple Related Integrals. ICML 2018: 5369-5378 - [i15]Xiaoyue Xi, François-Xavier Briol, Mark A. Girolami:
Bayesian Quadrature for Multiple Related Integrals. CoRR abs/1801.04153 (2018) - [i14]Jon Cockayne, Chris J. Oates, Mark A. Girolami:
A Bayesian Conjugate Gradient Method. CoRR abs/1801.05242 (2018) - [i13]François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic:
Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?". CoRR abs/1811.10275 (2018) - [i12]Richard Scalzo, David Kohn, Hugo K. H. Olierook, Gregory Houseman, Rohitash Chandra, Mark A. Girolami, Sally Cripps:
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. CoRR abs/1812.00318 (2018) - 2017
- [j65]Alexandros Beskos
, Mark A. Girolami
, Shiwei Lan
, Patrick E. Farrell, Andrew M. Stuart:
Geometric MCMC for infinite-dimensional inverse problems. J. Comput. Phys. 335: 327-351 (2017) - [j64]Patrick R. Conrad, Mark A. Girolami
, Simo Särkkä, Andrew M. Stuart, Konstantinos Zygalakis
:
Statistical analysis of differential equations: introducing probability measures on numerical solutions. Stat. Comput. 27(4): 1065-1082 (2017) - [c50]François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark A. Girolami:
On the Sampling Problem for Kernel Quadrature. ICML 2017: 586-595 - [c49]Chris J. Oates, Steven A. Niederer, Angela W. C. Lee, François-Xavier Briol, Mark A. Girolami:
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models. NIPS 2017: 110-118 - [i11]Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami:
Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems. CoRR abs/1701.04006 (2017) - [i10]Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami:
Bayesian Probabilistic Numerical Methods. CoRR abs/1702.03673 (2017) - [i9]Alessandro Barp, François-Xavier Briol, Anthony D. Kennedy, Mark A. Girolami:
Geometry and Dynamics for Markov Chain Monte Carlo. CoRR abs/1705.02891 (2017) - [i8]François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark A. Girolami:
On the Sampling Problem for Kernel Quadrature. CoRR abs/1706.03369 (2017) - 2016
- [j63]Shiwei Lan
, Tan Bui-Thanh
, Mike Christie, Mark A. Girolami
:
Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems. J. Comput. Phys. 308: 81-101 (2016) - [j62]Louis Ellam, Nicholas Zabaras, Mark A. Girolami
:
A Bayesian approach to multiscale inverse problems with on-the-fly scale determination. J. Comput. Phys. 326: 115-140 (2016) - [c48]Chris J. Oates, Mark A. Girolami:
Control Functionals for Quasi-Monte Carlo Integration. AISTATS 2016: 56-65 - [i7]Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami:
Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems. CoRR abs/1605.07811 (2016) - 2015
- [c47]Seppo Virtanen, Mark A. Girolami:
Ordinal Mixed Membership Models. ICML 2015: 588-596 - [c46]François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne:
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. NIPS 2015: 1162-1170 - [i6]Heiko Strathmann, Dino Sejdinovic, Mark A. Girolami:
Unbiased Bayes for Big Data: Paths of Partial Posteriors. CoRR abs/1501.03326 (2015) - [i5]Philipp Hennig, Michael A. Osborne, Mark A. Girolami:
Probabilistic Numerics and Uncertainty in Computations. CoRR abs/1506.01326 (2015) - [i4]François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic:
Probabilistic Integration. CoRR abs/1512.00933 (2015) - 2014
- [j61]Andrei Kramer, Vassilios Stathopoulos, Mark A. Girolami
, Nicole Radde:
mcmc_clib-an advanced MCMC sampling package for ode models. Bioinform. 30(20): 2991-2992 (2014) - [j60]Samuel Livingstone
, Mark A. Girolami
:
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions. Entropy 16(6): 3074-3102 (2014) - [j59]Maurizio Filippone
, Mark A. Girolami
:
Pseudo-Marginal Bayesian Inference for Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 36(11): 2214-2226 (2014) - [c45]Vassilios Stathopoulos, Veronica Zamora-Gutierrez, Kate E. Jones, Mark A. Girolami:
Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel. AISTATS 2014: 913-921 - [c44]Oisin Mac Aodha, Vassilios Stathopoulos, Gabriel J. Brostow, Michael Terry, Mark A. Girolami
, Kate E. Jones
:
Putting the Scientist in the Loop - Accelerating Scientific Progress with Interactive Machine Learning. ICPR 2014: 9-17 - [c43]Oana Andrei
, Muffy Calder
, Matthew Higgs, Mark A. Girolami
:
Probabilistic Model Checking of DTMC Models of User Activity Patterns. QEST 2014: 138-153 - [i3]Oana Andrei, Muffy Calder, Matthew Higgs, Mark A. Girolami:
Probabilistic Model Checking of DTMC Models of User Activity Patterns. CoRR abs/1403.6678 (2014) - 2013
- [j58]Maurizio Filippone
, Mingjun Zhong, Mark A. Girolami
:
A comparative evaluation of stochastic-based inference methods for Gaussian process models. Mach. Learn. 93(1): 93-114 (2013) - [j57]Tom Diethe
, Mark A. Girolami
:
Online Learning with (Multiple) Kernels: A Review. Neural Comput. 25(3): 567-625 (2013) - [c42]Matthew Higgs, Alistair Morrison
, Mark A. Girolami
, Matthew Chalmers:
Analysing user behaviour through dynamic population models. CHI Extended Abstracts 2013: 271-276 - [i2]Maurizio Filippone, Mark A. Girolami:
Exact-Approximate Bayesian Inference for Gaussian Processes. CoRR abs/1310.0740 (2013) - 2012
- [j56]Ke Yuan, Mark A. Girolami
, Mahesan Niranjan:
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations. Neural Comput. 24(6): 1462-1486 (2012) - [c41]Mingjun Zhong, Mark A. Girolami:
A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. ICML 2012 - [c40]Neil D. Lawrence, Mark A. Girolami:
Preface. AISTATS 2012 - [e6]Neil D. Lawrence, Mark A. Girolami:
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2012, La Palma, Canary Islands, Spain, April 21-23, 2012. JMLR Proceedings 22, JMLR.org 2012 [contents] - [i1]Mingjun Zhong, Mark A. Girolami:
A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. CoRR abs/1206.4666 (2012) - 2011
- [b1]Simon Rogers, Mark A. Girolami:
A First Course in Machine Learning. Chapman and Hall / CRC machine learning and pattern recognition series, CRC Press 2011, ISBN 978-1-43-982414-6, pp. I-XX, 1-285 - [j55]Tamara Polajnar, Theodoros Damoulas, Mark A. Girolami
:
Protein interaction sentence detection using multiple semantic kernels. J. Biomed. Semant. 2: 1 (2011) - [j54]Tamara Polajnar, Simon Rogers, Mark A. Girolami
:
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation. Int. J. Data Min. Bioinform. 5(1): 52-72 (2011) - [j53]Maurizio Filippone
, Antonietta Mira, Mark A. Girolami
:
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. 20(3): 295-297 (2011) - [c39]Roberto Paredes, Mark A. Girolami
:
On the Use of Diagonal and Class-Dependent Weighted Distances for the Probabilistic k-Nearest Neighbor. IbPRIA 2011: 265-272 - [c38]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
:
ITFoM - The IT Future of Medicine. FET 2011: 26-29 - [e5]Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski:
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science 6791, Springer 2011, ISBN 978-3-642-21734-0 [contents] - [e4]Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski:
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6792, Springer 2011, ISBN 978-3-642-21737-1 [contents] - 2010
- [j52]Mohammed Dakna, Keith Harris, Alexandros Kalousis, Sebastien Carpentier
, Walter Kolch
, Joost P. Schanstra
, Marion Haubitz, Antonia Vlahou
, Harald Mischak
, Mark A. Girolami
:
Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers. BMC Bioinform. 11: 594 (2010) - [j51]Simon Rogers, Arto Klami
, Janne Sinkkonen, Mark A. Girolami
, Samuel Kaski:
Infinite factorization of multiple non-parametric views. Mach. Learn. 79(1-2): 201-226 (2010) - [j50]Simon Rogers, Mark A. Girolami
, Tamara Polajnar:
Semi-parametric analysis of multi-rater data. Stat. Comput. 20(3): 317-334 (2010) - [j49]Ioannis Psorakis, Theodoros Damoulas, Mark A. Girolami
:
Multiclass relevance vector machines: sparsity and accuracy. IEEE Trans. Neural Networks 21(10): 1588-1598 (2010) - [p1]Mark Girolami, Ben Calderhead, Vladislav Vyshemirsky:
System Identification and Model Ranking: The Bayesian Perspective. Learning and Inference in Computational Systems Biology 2010: 201-230 - [e3]Neil D. Lawrence, Mark A. Girolami, Magnus Rattray, Guido Sanguinetti:
Learning and Inference in Computational Systems Biology. Computational molecular biology, MIT Press 2010, ISBN 978-0-262-01386-4 [contents]
2000 – 2009
- 2009
- [j48]Simon Rogers
, Richard A. Scheltema
, Mark A. Girolami
, Rainer Breitling
:
Probabilistic assignment of formulas to mass peaks in metabolomics experiments. Bioinform. 25(4): 512-518 (2009) - [j47]Ben Calderhead, Mark A. Girolami
:
Estimating Bayes factors via thermodynamic integration and population MCMC. Comput. Stat. Data Anal. 53(12): 4028-4045 (2009) - [j46]Theodoros Damoulas, Mark A. Girolami
:
Combining feature spaces for classification. Pattern Recognit. 42(11): 2671-2683 (2009) - [j45]Theodoros Damoulas, Mark A. Girolami
:
Pattern recognition with a Bayesian kernel combination machine. Pattern Recognit. Lett. 30(1): 46-54 (2009) - [c37]Yiming Ying, Colin Campbell, Mark A. Girolami:
Analysis of SVM with Indefinite Kernels. NIPS 2009: 2205-2213 - [c36]Rónán Daly, Kieron D. Edwards
, John S. O'Neill, J. Stuart Aitken, Andrew J. Millar
, Mark A. Girolami
:
Using Higher-Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana. PRIB 2009: 67-78 - [c35]Keith Harris, Mark A. Girolami
, Harald Mischak
:
Definition of Valid Proteomic Biomarkers: A Bayesian Solution. PRIB 2009: 137-149 - [c34]Keith Harris, Lisa McMillan, Mark A. Girolami
:
Inferring Meta-covariates in Classification. PRIB 2009: 150-161 - [c33]Tamara Polajnar, Mark A. Girolami
:
Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics. PRIB 2009: 270-281 - [c32]Tamara Polajnar, Simon Rogers, Mark A. Girolami
:
Classification of Protein Interaction Sentences via Gaussian Processes. PRIB 2009: 282-292 - [c31]Yiming Ying
, Colin Campbell, Theodoros Damoulas, Mark A. Girolami
:
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB 2009: 427-438 - [c30]Mingjun Zhong, Mark A. Girolami:
Reversible Jump MCMC for Non-Negative Matrix Factorization. AISTATS 2009: 663-670 - [e2]Visakan Kadirkamanathan
, Guido Sanguinetti, Mark A. Girolami, Mahesan Niranjan, Josselin Noirel:
Pattern Recognition in Bioinformatics, 4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009. Proceedings. Lecture Notes in Computer Science 5780, Springer 2009, ISBN 978-3-642-04030-6 [contents] - 2008
- [j44]Nicola Lama, Mark A. Girolami
:
vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R. Bioinform. 24(1): 135-136 (2008) - [j43]Vladislav Vyshemirsky, Mark A. Girolami
:
Bayesian ranking of biochemical system models. Bioinform. 24(6): 833-839 (2008) - [j42]Ian M. Overton, Gianandrea Padovani, Mark A. Girolami
, Geoffrey J. Barton
:
ParCrys: a Parzen window density estimation approach to protein crystallization propensity prediction. Bioinform. 24(7): 901-907 (2008) - [j41]Theodoros Damoulas, Mark A. Girolami
:
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection. Bioinform. 24(10): 1264-1270 (2008) - [j40]Vladislav Vyshemirsky, Mark A. Girolami
:
BioBayes: A software package for Bayesian inference in systems biology. Bioinform. 24(17): 1933-1934 (2008) - [j39]Vladislav Vyshemirsky, Mark A. Girolami
:
Bayesian ranking of biochemical system models. Bioinform. 24(20): 2421 (2008) - [j38]Simon Rogers
, Mark A. Girolami
, Walter Kolch
, Katrina M. Waters
, Tao Liu
, Brian Thrall, H. Steven Wiley
:
Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models. Bioinform. 24(24): 2894-2900 (2008) - [j37]Mingjun Zhong, Fabien Lotte
, Mark A. Girolami
, Anatole Lécuyer:
Classifying EEG for brain computer interfaces using Gaussian processes. Pattern Recognit. Lett. 29(3): 354-359 (2008) - [j36]Mark A. Girolami
:
Bayesian inference for differential equations. Theor. Comput. Sci. 408(1): 4-16 (2008) - [c29]Theodoros Damoulas, Yiming Ying
, Mark A. Girolami
, Colin Campbell:
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. ICMLA 2008: 577-582 - [c28]Ben Calderhead, Mark A. Girolami, Neil D. Lawrence:
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes. NIPS 2008: 217-224 - 2007
- [j35]Simon Rogers
, Raya Khanin, Mark A. Girolami
:
Bayesian model-based inference of transcription factor activity. BMC Bioinform. 8(S-2) (2007) - [j34]Dongshan Xing, Mark A. Girolami
:
Employing Latent Dirichlet Allocation for fraud detection in telecommunications. Pattern Recognit. Lett. 28(13): 1727-1734 (2007) - [j33]S. Manocha, Mark A. Girolami
:
An empirical analysis of the probabilistic K-nearest neighbour classifier. Pattern Recognit. Lett. 28(13): 1818-1824 (2007) - [c27]Oliver Sharma, Mark A. Girolami
, Joseph S. Sventek:
Detecting worm variants using machine learning. CoNEXT 2007: 2 - [c26]Simon Rogers, Mark A. Girolami:
Multi-class Semi-supervised Learning with the e-truncated Multinomial Probit Gaussian Process. Gaussian Processes in Practice 2007: 17-32 - 2006
- [j32]Mark A. Girolami
, Simon Rogers:
Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. Neural Comput. 18(8): 1790-1817 (2006) - [j31]Anna Szymkowiak-Have, Mark A. Girolami
, Jan Larsen
:
Clustering via kernel decomposition. IEEE Trans. Neural Networks 17(1): 256-264 (2006) - [c25]Gavin C. Cawley, Nicola L. C. Talbot, Mark A. Girolami:
Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation. NIPS 2006: 209-216 - [c24]Mark A. Girolami, Mingjun Zhong:
Data Integration for Classification Problems Employing Gaussian Process Priors. NIPS 2006: 465-472 - [c23]Robert Jenssen, Torbjørn Eltoft, Mark A. Girolami, Deniz Erdogmus:
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm. NIPS 2006: 633-640 - 2005
- [j30]Simon Rogers
, Mark A. Girolami
:
A Bayesian regression approach to the inference of regulatory networks from gene expression data. Bioinform. 21(14): 3131-3137 (2005) - [j29]Mark A. Girolami
, Ata Kabán:
Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains. Data Min. Knowl. Discov. 10(3): 175-196 (2005) - [j28]Simon Rogers, Mark A. Girolami, Colin Campbell, Rainer Breitling:
The Latent Process Decomposition of cDNA Microarray Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 2(2): 143-156 (2005) - [c22]Simon Rogers, Mark A. Girolami
, Ronald Krebs, Harald Mischak:
Disease Classification from Capillary Electrophoresis: Mass Spectrometry. ICAPR (1) 2005: 183-191 - [c21]Mark A. Girolami
, Simon Rogers:
Hierarchic Bayesian models for kernel learning. ICML 2005: 241-248 - [c20]Leif Azzopardi, Mark A. Girolami
, Malcolm K. Crowe
:
Probabilistic hyperspace analogue to language. SIGIR 2005: 575-576 - 2004
- [j27]Mark A. Girolami
, Rainer Breitling
:
Biologically valid linear factor models of gene expression. Bioinform. 20(17): 3021-3033 (2004) - [j26]Chao He, Mark A. Girolami
, Gary Ross:
Employing optimized combinations of one-class classifiers for automated currency validation. Pattern Recognit. 37(6): 1085-1096 (2004) - [j25]Chao He, Mark A. Girolami
:
Novelty detection employing an L2 optimal non-parametric density estimator. Pattern Recognit. Lett. 25(12): 1389-1397 (2004) - [c19]Ali Al-Shahib, Chao He, Aik Choon Tan, Mark A. Girolami
, David R. Gilbert:
An Assessment of Feature Relevance in Predicting Protein Function from Sequence. IDEAL 2004: 52-57 - [c18]Leif Azzopardi, Mark A. Girolami, Cornelis Joost van Rijsbergen:
User biased document language modelling. SIGIR 2004: 542-543 - 2003
- [j24]Ella Bingham
, Ata Kabán, Mark A. Girolami
:
Topic Identification in Dynamical Text by Complexity Pursuit. Neural Process. Lett. 17(1): 69-83 (2003) - [j23]Mark A. Girolami
, Chao He:
Probability Density Estimation from Optimally Condensed Data Samples. IEEE Trans. Pattern Anal. Mach. Intell. 25(10): 1253-1264 (2003) - [c17]Mark A. Girolami, Ata Kabán:
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles. NIPS 2003: 9-16 - [c16]Leif Azzopardi, Mark A. Girolami, Keith van Rijsbergen:
Investigating the relationship between language model perplexity and IR precision-recall measures. SIGIR 2003: 369-370 - [c15]