Mark A. Girolami
Orcid: 0000-0003-3008-253XAffiliations:
- University of Cambridge, UK
According to our database1,
Mark A. Girolami
authored at least 177 papers
between 1996 and 2024.
Collaborative distances:
Collaborative distances:
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Online presence:
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on turing.ac.uk
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on twitter.com
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on orcid.org
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on id.loc.gov
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on d-nb.info
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on dl.acm.org
On csauthors.net:
Bibliography
2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
SIAM/ASA J. Uncertain. Quantification, December, 2023
J. Comput. Phys., October, 2023
Trans. Mach. Learn. Res., 2023
Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning.
Comput. Aided Civ. Infrastructure Eng., 2023
Proceedings of the International Conference on Machine Learning, 2023
Incorporating Reliability in Graph Information Propagation by Fluid Dynamics Diffusion: A case of Multimodal Semisupervised Deep Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Anomaly detection in streaming data with gaussian process based stochastic differential equations.
Pattern Recognit. Lett., 2022
Pattern Recognit. Lett., 2022
SIAM/ASA J. Uncertain. Quantification, 2022
J. Comput. Phys., 2022
$Φ$-DVAE: Learning Physically Interpretable Representations with Nonlinear Filtering.
CoRR, 2022
CoRR, 2022
Knowledge Transfer in Engineering Fleets: Hierarchical Bayesian Modelling for Multi-Task Learning.
CoRR, 2022
CoRR, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Math. Comput., 2021
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness.
J. Mach. Learn. Res., 2021
Uncertainty quantification for data-driven turbulence modelling with Mondrian forests.
J. Comput. Phys., 2021
A graph representation based on fluid diffusion model for multimodal data analysis: theoretical aspects and enhanced community detection.
CoRR, 2021
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction.
CoRR, 2021
A Self-Sensing Digital Twin of a Railway Bridge using the Statistical Finite Element Method.
CoRR, 2021
2020
Comput. Stat. Data Anal., 2020
Continuous calibration of a digital twin: comparison of particle filter and Bayesian calibration approaches.
CoRR, 2020
Convergence Guarantees for Gaussian Process Approximations Under Several Observation Models.
CoRR, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
The synthesis of data from instrumented structures and physics-based models via Gaussian processes.
J. Comput. Phys., 2019
Embedded Ridge Approximations: Constructing Ridge Approximations Over Localized Scalar Fields For Improved Simulation-Centric Dimension Reduction.
CoRR, 2019
CoRR, 2019
A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability.
IEEE Access, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
PLoS Comput. Biol., 2018
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success.
CoRR, 2018
CoRR, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Statistical analysis of differential equations: introducing probability measures on numerical solutions.
Stat. Comput., 2017
CoRR, 2017
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems.
J. Comput. Phys., 2016
A Bayesian approach to multiscale inverse problems with on-the-fly scale determination.
J. Comput. Phys., 2016
Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems.
CoRR, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
IEEE Trans. Pattern Anal. Mach. Intell., 2014
Entropy, 2014
Proceedings of the Quantitative Evaluation of Systems - 11th International Conference, 2014
Putting the Scientist in the Loop - Accelerating Scientific Progress with Interactive Machine Learning.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014
Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
2013
A comparative evaluation of stochastic-based inference methods for Gaussian process models.
Mach. Learn., 2013
Proceedings of the 2013 ACM SIGCHI Conference on Human Factors in Computing Systems, 2013
2012
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations.
Neural Comput., 2012
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Proceedings of the 29th International Conference on Machine Learning, 2012
2011
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., 2011
Proceedings of the 2nd European Future Technologies Conference and Exhibition, 2011
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation.
Int. J. Data Min. Bioinform., 2011
J. Biomed. Semant., 2011
On the Use of Diagonal and Class-Dependent Weighted Distances for the Probabilistic k-Nearest Neighbor.
Proceedings of the Pattern Recognition and Image Analysis - 5th Iberian Conference, 2011
Chapman and Hall / CRC machine learning and pattern recognition series, CRC Press, ISBN: 978-1-43-982414-6, 2011
2010
IEEE Trans. Neural Networks, 2010
BMC Bioinform., 2010
System Identification and Model Ranking: The Bayesian Perspective.
Proceedings of the Learning and Inference in Computational Systems Biology., 2010
2009
Pattern Recognit. Lett., 2009
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
Comput. Stat. Data Anal., 2009
Bioinform., 2009
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm.
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics.
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Using Higher-Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana.
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
2008
Pattern Recognit. Lett., 2008
Bioinform., 2008
Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models.
Bioinform., 2008
ParCrys: a Parzen window density estimation approach to protein crystallization propensity prediction.
Bioinform., 2008
vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R.
Bioinform., 2008
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection.
Bioinform., 2008
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008
2007
Pattern Recognit. Lett., 2007
Pattern Recognit. Lett., 2007
Multi-class Semi-supervised Learning with the e-truncated Multinomial Probit Gaussian Process.
Proceedings of the Gaussian Processes in Practice, 2007
BMC Bioinform., 2007
Proceedings of the 2007 ACM Conference on Emerging Network Experiment and Technology, 2007
2006
Neural Comput., 2006
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
2005
IEEE ACM Trans. Comput. Biol. Bioinform., 2005
Data Min. Knowl. Discov., 2005
A Bayesian regression approach to the inference of regulatory networks from gene expression data.
Bioinform., 2005
Proceedings of the SIGIR 2005: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005
Proceedings of the Machine Learning, 2005
Proceedings of the Pattern Recognition and Data Mining, 2005
2004
Pattern Recognit. Lett., 2004
Employing optimized combinations of one-class classifiers for automated currency validation.
Pattern Recognit., 2004
Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004
Proceedings of the Intelligent Data Engineering and Automated Learning, 2004
2003
IEEE Trans. Pattern Anal. Mach. Intell., 2003
Neural Process. Lett., 2003
Proceedings of the SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28, 2003
Investigating the relationship between language model perplexity and IR precision-recall measures.
Proceedings of the SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28, 2003
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
2002
SIGMOD Rec., 2002
Report on the 24th European colloquium on information retrieval research (ECIR 2002).
SIGIR Forum, 2002
Neural Process. Lett., 2002
Neural Comput., 2002
A Probabilistic Framework for the Hierarchic Organisation and Classification of Document Collections.
J. Intell. Inf. Syst., 2002
J. Intell. Inf. Syst., 2002
Latent variable models for the topographic organisation of discrete and strictly positive data.
Neurocomputing, 2002
A General Framework for a Principled Hierarchical Visualization of Multivariate Data.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2002
2001
The topographic organization and visualization of binary data using multivariate-Bernoulli latent variable models.
IEEE Trans. Neural Networks, 2001
A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2001
Neural Comput., 2001
Neural Comput., 2001
Neural Comput. Appl., 2001
Proceedings of the Poster Proceedings of the Tenth International World Wide Web Conference, 2001
2000
Probabilistic Hierarchical Clustering Method for Organizing Collections of Text Documents.
Proceedings of the 15th International Conference on Pattern Recognition, 2000
Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents.
Proceedings of the 15th International Conference on Pattern Recognition, 2000
A generative model for sparse discrete binary data with non-uniform categorical priors.
Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000
Proceedings of the 11th International Workshop on Database and Expert Systems Applications (DEXA'00), 2000
Kernel PCA Feature Extraction of Event-Related Potentials for Human Signal Detection Performance.
Proceedings of the Artificial Neural Networks in Medicine and Biology, 2000
Proceedings of the Artificial Neural Networks in Medicine and Biology, 2000
1999
Blind source separation of more sources than mixtures using overcomplete representations.
IEEE Signal Process. Lett., 1999
Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources.
Neural Comput., 1999
1998
A common neural-network model for unsupervised exploratory data analysis and independent component analysis.
IEEE Trans. Neural Networks, 1998
The Latent Variable Data Model for Exploratory Data Analysis and Visualisation: A Generalisation of the Nonlinear Infomax Algorithm.
Neural Process. Lett., 1998
Neural Comput., 1998
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998
1997
An extended exploratory projection pursuit network with linear and nonlinear anti-hebbian lateral connections applied to the cocktail party problem.
Neural Networks, 1997
Int. J. Neural Syst., 1997
Generalised independent component analysis through unsupervised learning with emergent Bussgang properties.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997
Kurtosis extrema and identification of independent components: a neural network approach.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997
Fahlman-Type Activation Functions Applied to Nonlinear PCA Networks Provide a Generalised Independent Component Analysis.
Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, 1997
Principal Components Identify MLP Hidden Layer Size for Optimal Generalisation Performance.
Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, 1997
Proceedings of the 5th Eurorean Symposium on Artificial Neural Networks, 1997
1996