Mark Girolami | Academic Influence

Q: What Schools Are Affiliated With Mark Girolami

Mark Girolami is affiliated with the following schools: University of Warwick, Imperial College London, University College London, Helsinki University of Technology, University of the West of Scotland, University of Glasgow, University of Cambridge

Why Is Mark Girolami Influential?

(Suggest an Edit or Addition)

According to Wikipedia, Mark A. Girolami is a British civil engineer, statistician and data engineer. He has held the Sir Kirby Laing Professorship of Civil Engineering in the Department of Engineering at the University of Cambridge since 2019. He has been the chief scientist of the Alan Turing Institute since 2021. He is a Fellow of Christ's College, Cambridge, and winner of a Royal Society Wolfson Research Merit Award. Girolami is a founding editor of the journal Data-Centric Engineering, and also served as the program director for data-centric engineering at Turing.

(See a Problem?)

Mark Girolami's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources (1999) (1770)
Riemann manifold Langevin and Hamiltonian Monte Carlo methods (2011) (1285)
Mercer kernel-based clustering in feature space (2002) (911)
Blind source separation of more sources than mixtures using overcomplete representations (1999) (475)
Naturally Occurring Human Urinary Peptides for Use in Diagnosis of Chronic Kidney Disease* (2010) (425)
A Unifying Information-Theoretic Framework for Independent Component Analysis (2000) (412)
Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources (1999) (337)
Hamiltonian Monte Carlo for Hierarchical Models (2013) (312)
Clinical proteomics: A need to define the field and to begin to set adequate standards (2007) (303)
Recommendations for Biomarker Identification and Qualification in Clinical Proteomics (2010) (298)
Advances in urinary proteome analysis and biomarker discovery. (2007) (278)
Probabilistic numerics and uncertainty in computations (2015) (267)
Probability Density Estimation from Optimally Condensed Data Samples (2003) (229)
On an equivalence between PLSI and LDA (2003) (229)
Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression (2001) (221)
Bayesian ranking of biochemical system models (2008) (220)
Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors (2006) (216)
Control functionals for Monte Carlo integration (2014) (208)
A Variational Method for Learning Sparse and Overcomplete Representations (2001) (207)
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes (2008) (196)
Estimating Bayes factors via thermodynamic integration and population MCMC (2009) (180)
A First Course in Machine Learning (2011) (179)
Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation (2006) (175)
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection (2008) (173)
Orthogonal Series Density Estimation and the Kernel Eigenvalue Problem (2002) (163)
The Geometric Foundations of Hamiltonian Monte Carlo (2014) (158)
Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models (2008) (155)
Investigating the relationship between language model perplexity and IR precision-recall measures (2003) (150)
Bat detective—Deep learning tools for bat acoustic signal detection (2017) (135)
Advances in Independent Component Analysis (2000) (135)
Multiclass Relevance Vector Machines: Sparsity and Accuracy (2010) (135)
Bayesian Probabilistic Numerical Methods (2017) (134)
Geodesic Monte Carlo on Embedded Manifolds (2013) (133)
An Alternative Perspective on Adaptive Independent Component Analysis Algorithms (1998) (125)
A Bayesian regression approach to the inference of regulatory networks from gene expression data (2005) (124)
On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods (2013) (122)
Bayesian Solution Uncertainty Quantification for Differential Equations (2013) (122)
Probabilistic Integration: A Role in Statistical Computation? (2015) (121)
Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers (2010) (117)
Bayesian inference for differential equations (2008) (115)
Construction with digital twin information systems (2020) (114)
Riemann Manifold Langevin and Hamiltonian Monte Carlo (2010) (113)
The latent process decomposition of cDNA microarray data sets (2005) (109)
Geometric MCMC for infinite-dimensional inverse problems (2016) (106)
On the geometric ergodicity of Hamiltonian Monte Carlo (2016) (104)
Langevin diffusions and the Metropolis-adjusted Langevin algorithm (2013) (99)
How Deep Are Deep Gaussian Processes? (2017) (99)
Classifying EEG for brain computer interfaces using Gaussian processes (2008) (98)
Probabilistic assignment of formulas to mass peaks in metabolomics experiments (2009) (95)
Inferring signaling pathway topologies from multiple perturbation measurements of specific biochemical species. (2010) (94)
An empirical analysis of the probabilistic K-nearest neighbour classifier (2007) (91)
Employing Latent Dirichlet Allocation for fraud detection in telecommunications (2007) (88)
Hierarchic Bayesian models for kernel learning (2005) (86)
Negentropy and Kurtosis as Projection Pursuit Indices Provide Generalised ICA Algorithms (1996) (86)
Analysis of free text in electronic health records for identification of cancer patient trajectories (2017) (84)
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees (2015) (83)
Learning and Inference in Computational Systems Biology (2010) (80)
Statistical analysis of differential equations: introducing probability measures on numerical solutions (2016) (78)
Decoding post-stroke motor function from structural brain imaging (2016) (76)
Topic based language models for ad hoc information retrieval (2004) (74)
Inferring Signaling Pathway Topologies from Multiple Perturbation Measurements of Specific Biochemical Species (2010) (73)
ParCrys: a Parzen window density estimation approach to protein crystallization propensity prediction (2008) (70)
Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian Monte Carlo (2014) (70)
Optimizing The Integrator Step Size for Hamiltonian Monte Carlo (2014) (69)
Self-Organising Neural Networks: Independent Component Analysis and Blind Source Separation (1999) (69)
BioBayes: A software package for Bayesian inference in systems biology (2008) (67)
A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data (2001) (66)
Bayesian model-based inference of transcription factor activity (2007) (66)
Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems (2017) (65)
Pseudo-Marginal Bayesian Inference for Gaussian Processes (2013) (64)
Probabilistic Integration: A Role for Statisticians in Numerical Analysis? (2015) (63)
Analysis of SVM with Indefinite Kernels (2009) (60)
An Expectation-Maximization Approach to Nonlinear Component Analysis (2001) (60)
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights (2021) (59)
Building Information Modelling, Artificial Intelligence and Construction Tech (2020) (58)
Minimum Stein Discrepancy Estimators (2019) (58)
A common neural-network model for unsupervised exploratory data analysis and independent component analysis (1998) (58)
A comparative evaluation of stochastic-based inference methods for Gaussian process models (2013) (56)
Convergence rates for a class of estimators based on Stein’s method (2016) (56)
Statistical analysis of nonlinear dynamical systems using differential geometric sampling methods (2011) (55)
Scaling digital twins from the artisanal to the industrial (2021) (55)
A Probabilistic Framework for the Hierarchic Organisation and Classification of Document Collections (2002) (54)
Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems (2015) (54)
Combining feature spaces for classification (2009) (53)
Topic Identification in Dynamical Text by Complexity Pursuit (2003) (53)
Extraction of independent signal sources using a deflationary exploratory projection pursuit network (1997) (52)
Regulation of post-Golgi LH3 trafficking is essential for collagen homeostasis (2016) (52)
Markov chain Monte Carlo inference for Markov jump processes via the linear noise approximation (2012) (51)
The Controlled Thermodynamic Integral for Bayesian Model Evidence Evaluation (2016) (50)
Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment (2017) (49)
Hyperpriors for Matérn fields with applications in Bayesian inversion (2016) (47)
Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems (2016) (46)
A Digital Twin of Bridges for Structural Health Monitoring (2019) (46)
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions (2014) (45)
In vivo multiplex molecular imaging of vascular inflammation using surface-enhanced Raman spectroscopy (2018) (45)
Riemannian Manifold Hamiltonian Monte Carlo (2009) (43)
Generalised independent component analysis through unsupervised learning with emergent Bussgang properties (1997) (43)
Statistical Inference for Generative Models with Maximum Mean Discrepancy (2019) (43)
Stein Point Markov Chain Monte Carlo (2019) (43)
Markov Chain Monte Carlo from Lagrangian Dynamics (2015) (43)
Automated, High Accuracy Classification of Parkinsonian Disorders: A Pattern Recognition Approach (2013) (42)
Analysis of complex, multidimensional datasets. (2006) (42)
A Bayesian approach to multiscale inverse problems with on-the-fly scale determination (2016) (41)
Systems biology: opening new avenues in clinical research. (2010) (41)
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles (2003) (41)
Accurate Prediction of BRCA1 and BRCA2 Heterozygous Genotype Using Expression Profiling after Induced DNA Damage (2006) (40)
Data Integration for Classification Problems Employing Gaussian Process Priors (2006) (40)
Stochastic ICA Contrast Maximisation Using Oja's Nonlinear PCA Algorithm (1997) (39)
Zero Variance Differential Geometric Markov Chain Monte Carlo Algorithms (2014) (38)
EWS-FLI1 employs an E2F switch to drive target gene expression (2015) (38)
Biologically valid linear factor models of gene expression (2004) (38)
PROBABILISTIC PREDICTION OF NEUROLOGICAL DISORDERS WITH A STATISTICAL ASSESSMENT OF NEUROIMAGING DATA MODALITIES. (2012) (38)
Bayesian Uncertainty Quantification for Differential Equations (2013) (37)
A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams (2002) (37)
An extended exploratory projection pursuit network with linear and nonlinear anti-hebbian lateral connections applied to the cocktail party problem (1997) (37)
Pattern recognition with a Bayesian kernel combination machine (2009) (36)
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins (2008) (36)
Population MCMC methods for history matching and uncertainty quantification (2010) (35)
Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains (2005) (35)
Employing optimized combinations of one-class classifiers for automated currency validation (2004) (35)
Bayesian Quadrature for Multiple Related Integrals (2018) (33)
Lagrangian Dynamical Monte Carlo (2012) (33)
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm (2006) (33)
Online Learning with (Multiple) Kernels: A Review (2013) (31)
Bayesian Statistical Inference in Ion-Channel Models with Exact Missed Event Correction. (2016) (31)
Geometry and Dynamics for Markov Chain Monte Carlo (2017) (30)
ADVANCES IN MICROBIAL SYSTEMS BIOLOGY (2014) (30)
The silicon trypanosome (2010) (29)
The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions (2019) (28)
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness (2020) (27)
Multi-resolution Multi-task Gaussian Processes (2019) (27)
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success (2018) (27)
Playing Russian Roulette with Intractable Likelihoods (2013) (26)
Clustering via kernel decomposition (2006) (26)
Stochastic modelling of urban structure (2018) (26)
Control Functionals for Quasi-Monte Carlo Integration (2015) (26)
The topographic organization and visualization of binary data using multivariate-Bernoulli latent variable models (2001) (26)
A probabilistic hierarchical clustering method for organising collections of text documents (2000) (26)
Posterior inference for sparse hierarchical non-stationary models (2018) (26)
Reversible Jump MCMC for Non-Negative Matrix Factorization (2009) (25)
Probabilistic hyperspace analogue to language (2005) (25)
On the Sampling Problem for Kernel Quadrature (2017) (25)
Identification of prognostic signatures in breast cancer microarray data using Bayesian techniques (2006) (25)
A Bayesian Conjugate Gradient Method (2018) (24)
The geometric foundations of Hamiltonian (2017) (24)
Systems biology to battle vascular disease. (2010) (23)
Putting the Scientist in the Loop -- Accelerating Scientific Progress with Interactive Machine Learning (2014) (21)
Semi-parametric analysis of multi-rater data (2010) (21)
Multi-class Semi-supervised Learning with the e-truncated Multinomial Probit Gaussian Process (2007) (21)
Kernel PCA Feature Extraction of Event-Related Potentials for Human Signal Detection Performance (2000) (21)
Probability Measures for Numerical Solutions of Differential Equations (2015) (20)
Novelty detection employing an L2 optimal non-parametric density estimator (2004) (20)
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models (2016) (19)
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations (2012) (19)
A Riemannian-Stein Kernel method (2018) (19)
Bayesian methods to detect dye‐labelled DNA oligonucleotides in multiplexed Raman spectra (2011) (18)
Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry (2016) (17)
Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus (2002) (17)
A First Course in Machine Learning, Second Edition (2016) (17)
Unbiased Bayes for Big Data: Paths of Partial Posteriors (2015) (17)
The role of statistics in data-centric engineering (2018) (17)
ITFoM - The IT Future of Medicine (2011) (17)
Document Classification Employing the Fisher Kernel Derived from Probabilistic Hierarchic Corpus Rep (2001) (16)
BRCA1 and BRCA2 Missense Variants of High and Low Clinical Significance Influence Lymphoblastoid Cell Line Post-Irradiation Gene Expression (2008) (16)
Bat echolocation call identification for biodiversity monitoring: a probabilistic approach (2018) (16)
Preferential Attachment of Specific Fluorescent Dyes and Dye Labeled DNA Sequences in a Surface Enhanced Raman Scattering Multiplex. (2016) (16)
Latent variable models for the topographic organisation of discrete and strictly positive data (2002) (16)
vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R (2008) (16)
Digital twin of an urban-integrated hydroponic farm (2020) (16)
Self-Organising Neural Networks (1999) (15)
Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel (2014) (15)
The Controlled Thermodynamic Integral for Bayesian Model Comparison (2014) (15)
Handbook of Statistical Systems Biology: Stumpf/Handbook of Statistical Systems Biology (2011) (15)
Infinite factorization of multiple non-parametric views (2010) (15)
Detecting worm variants using machine learning (2007) (14)
Initialized and guided EM-clustering of sparse binary data with application to text based documents (2000) (14)
A Unifying and Canonical Description of Measure-Preserving Diffusions (2021) (14)
Semi-Exact Control Functionals From Sard’s Method (2020) (14)
Finding Topics in Dynamical Text: Application to Chat Line Discussions (2001) (14)
Handbook of Statistical Systems Biology (2011) (13)
Extraction of Sleep-Spindles from the Electroencephalogram (EEG) (2000) (13)
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents (2022) (13)
A Bayesian Conjugate Gradient Method (with Discussion) (2019) (13)
Variational Bayesian Multinomial Probit Regression with (2006) (13)
A Riemann–Stein kernel method (2018) (13)
Probabilistic Numerical Methods for Partial Differential Equations and Bayesian Inverse Problems ∗ (2018) (13)
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation (2011) (12)
A nonlinear model of the binaural cocktail party effect (1998) (11)
Quantification of Functionalised Gold Nanoparticle-Targeted Knockdown of Gene Expression in HeLa Cells (2014) (11)
Optimization on manifolds: A symplectic approach (2021) (11)
PeriPy - A High Performance OpenCL Peridynamics Package (2021) (11)
Propagative broad learning for nonparametric modeling of ambient effects on structural health indicators (2020) (11)
Probabilistic Model Checking of DTMC Models of User Activity Patterns (2014) (11)
Protein interaction sentence detection using multiple semantic kernels (2011) (11)
Predictive response-relevant clustering of expression data provides insights into disease processes (2010) (11)
Statistical finite elements for misspecified models (2020) (11)
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm (2009) (10)
Bayesian modelling and quantification of Raman spectroscopy (2016) (10)
Bayesian approaches for mechanistic ion channel modeling. (2013) (10)
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I (2011) (10)
Using Higher-Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana (2009) (10)
Kurtosis extrema and identification of independent components: a neural network approach (1997) (10)
Integration in reproducing kernel Hilbert spaces of Gaussian kernels (2020) (9)
Noise reduction and speech enhancement via temporal anti-Hebbian learning (1998) (9)
IMPLEMENTING DECISIONS IN BINARY DECISION TREES USING INDEPENDENT COMPONENT ANALYSIS (2007) (9)
A Unifying Information-theoretic Framework forIndependent Component (1998) (9)
Bayesian Data Fusion with Gaussian Process Priors : An Application to Protein Fold Recognition ? (2006) (9)
Fourth Order Cumulant Based Blind Source Separation (1999) (9)
Convergence Guarantees for Gaussian Process Approximations Under Several Observation Models (2020) (8)
A temporal model of linear anti-Hebbian learning (1996) (8)
Hamiltonian Monte Carlo on Symmetric and Homogeneous Spaces via Symplectic Reduction (2019) (8)
Symmetric adaptive maximum likelihood estimation for noise cancellation and signal separation (1997) (8)
A generative model for sparse discrete binary data with non-uniform categorical priors (2000) (8)
System Identification and Model Ranking: The Bayesian Perspective (2010) (7)
5. Optimality criteria for probabilistic numerical methods (2019) (7)
The synthesis of data from instrumented structures and physics-based models via Gaussian processes (2018) (7)
Self-Organizing Neural Networks (1999) (7)
Higher Order Cumulant Maximisation using Non-linear Hebbian and Anti-Hebbian Learning for Adaptive Blind Separation of Source Signals (1996) (7)
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09) (2009) (7)
Digital twinning of self-sensing structures using the statistical finite element method (2021) (6)
Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?" (2018) (6)
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction (2021) (6)
Embedded ridge approximations (2019) (6)
A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability (2019) (6)
A data-centric approach to generative modelling for 3D-printed steel (2021) (6)
The silicon trypanosome: a test case of iterative model extension in systems biology. (2014) (6)
A General Framework for a Principled Hierarchical Visualization of Multivariate Data (2002) (6)
Advances in Information Retrieval (2002) (6)
Anomaly detection in a fleet of industrial assets with hierarchical statistical modeling (2020) (6)
Continuous calibration of a digital twin: Comparison of particle filter and Bayesian calibration approaches (2020) (6)
Multi-fidelity approach to Bayesian parameter estimation in subsurface heat and fluid transport models. (2020) (6)
Definition of Valid Proteomic Biomarkers: A Bayesian Solution (2009) (6)
Real-time statistical modelling of data generated from self-sensing bridges (2018) (6)
The Topographic Organisation and Visulisation of Binary Data using Mutivariate-Bernoulli Latent Variable Models (2001) (6)
Variational Bayesian approximation of inverse problems using sparse precision matrices (2021) (5)
mcmc_clib-an advanced MCMC sampling package for ode models (2014) (5)
Latent class and trait models for data classification and visualisation (2001) (5)
Ordinal Mixed Membership Models (2015) (5)
Probabilistic Integration : A Role in Statistical Computation ? 1 (2019) (5)
Model selection and sensitivity analysis in the biomechanics of soft tissues: a case study on the human knee meniscus (2021) (5)
Precision-Recall Balanced Topic Modelling (2019) (5)
Manifold MCMC for Mixtures (2011) (5)
Exact-Approximate Bayesian Inference for Gaussian Processes (2013) (5)
Unique Reporter-Based Sensor Platforms to Monitor Signalling in Cells (2012) (5)
Analysing user behaviour through dynamic population models (2013) (5)
Probabilistic Integration (2015) (5)
Posterior Integration on a Riemannian Manifold (2017) (4)
Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation" (2012) (4)
Low-rank statistical finite elements for scalable model-data synthesis (2021) (4)
Supplementary Material for “ A Bayesian Conjugate-Gradient Method ” (2018) (4)
A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices (2012) (4)
Bayesian assessments of aeroengine performance with transfer learning (2020) (4)
Lagrangian Manifold Monte Carlo on Monge Patches (2022) (4)
Independence is far from normal (1997) (4)
On the Fully Bayesian Treatment of Latent Gaussian Models using Stochastic Simulations (2012) (4)
ADAPTIVE PROCESSING SCHEMES INSPIRED BY BINAURAL UNMASKING FOR ENHANCEMENT OF SPEECH CORRUPTED WITH NOISE AND REVERBERATION (1998) (3)
Disease Classification from Capillary Electrophoresis: Mass Spectrometry (2005) (3)
Report on the 24th European colloquium on information retrieval research (ECIR 2002) (2002) (3)
The Latent Variable Data Model for Exploratory Data Analysis and Visualisation: A Generalisation of the Nonlinear Infomax Algorithm (1998) (3)
Inferring Meta-covariates in Classification (2009) (3)
Dynamic content based ranking (2020) (3)
Statistical methods to enable practical on-site tomographic imaging of whole-core samples (2018) (3)
Targeted Separation and Convergence with Kernel Discrepancies (2022) (3)
Classification of Protein Interaction Sentences via Gaussian Processes (2009) (3)
Proceedings of the 24th BCS-IRSG European Colloquium on IR Research: Advances in Information Retrieval (2002) (3)
Advances in Neural Information Processing Systems 19 (NIPS 2006) (2007) (3)
Uncertainty Quantification of Density and Stratification Estimates with Implications for Predicting Ocean Dynamics (2019) (3)
An Assessment of Feature Relevance in Predicting Protein Function from Sequence (2004) (3)
Accelerating Quasi-Monte Carlo in Reproducing Kernel Hilbert Spaces (2015) (3)
Advances in Information Retrieval: 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25-27, 2002 Proceedings (2002) (3)
A Bayesian Analysis of the ERK Signalling Pathway (2006) (3)
Uncertainty quantification for data-driven turbulence modelling with Mondrian forests (2020) (3)
Model based identification of transcription factor activity from microarray data (2006) (3)
The Statistical Finite Element Method (2019) (3)
Broad learning robust semi-active structural control: A nonparametric approach (3)
Variance Reduction for Quasi-Monte Carlo (2015) (3)
Comprar Handbook Of Statistical Systems Biology | Michael P. H. Stumpf | 9780470710869 | Wiley (2011) (3)
Bayesian Numerical Methods as a Case Study for Statistical Data Science (2018) (2)
Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009) (2)
Unbiased local solutions of partial differential equations via the Feynman-Kac Identities (2016) (2)
Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian (2014) (2)
A Self-Sensing Digital Twin of a Railway Bridge using the Statistical Finite Element Method (2021) (2)
Neural parameter calibration for large-scale multiagent models (2022) (2)
Anomaly detection in streaming data with gaussian process based stochastic differential equations (2021) (2)
Monte Carlo methods and zero variance principle (2015) (2)
Phylogenetic Gaussian Processes for Bat Echolocation (2018) (2)
Bayesian Uncertainty Quantication for Dierential Equations (2014) (2)
User biased document language modelling (2004) (2)
Probabilistic Integration and Intractable Distributions (2016) (2)
Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs (2022) (2)
Phylogenetic Gaussian Processes for Bat Echolocation (2018) (2)
Inference for Gaussian process emulation of oil reservoir simulation codes (2010) (2)
Bayesian learning via neural Schrödinger–Föllmer flows (2021) (2)
The organisation and visualisation of document corpora: a probabilistic approach (2000) (2)
Statistical Finite Elements via Langevin Dynamics (2021) (2)
Phylogenetic Gaussian Processes for Bat Echolocation (2018) (2)
Proceedings of the 21th international conference on Artificial neural networks - Volume Part I (2011) (2)
Addressing the challenge of dening valid proteomic biomarkers and classiers. (2011) (2)
Kernel PCA for Feature Extra tion and De-Noisingin Non-linear (2000) (2)
Combining Information with a Bayesian Multi-class Multi-kernel Pattern Recognition Machine (2010) (1)
Spatio‐temporal mixed membership models for criminal activity (2021) (1)
Rejoinder: Geodesic Monte Carlo on Embedded Manifolds (2014) (1)
Uncovering smartphone usage patterns with multi‐view mixed membership models (2016) (1)
Technical Report An Evaluation of Gaussian Processes for Sentence Classication and Protein Interaction Detection (2008) (1)
Using Expert Knowledge to Generate Data for Broadband Line Prognostics Under Limited Failure Data Availability (2020) (1)
Variance Reduction for QMC in Reproducing Kernel Hilbert Spaces (2015) (1)
Artificial Neural Networks and Machine Learning Research - ICANN 2011, Part II (2011) (1)
Accurate prediction of BRCA1 and BRCA2 heterozygous genotypes using expression profiling of lymphocytes after irradiation-induced DNA damage (2008) (1)
Proceedings of the 29 th International Conference on Machine Learning, Edinburgh, Scotland, UK, 2012 (2012) (1)
Temporal Anti-Hebbian Learning (1999) (1)
Statistical analysis of differential equations: introducing probability measures on numerical solutions (2016) (1)
Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics (2009) (1)
Theoretical Guarantees for the Statistical Finite Element Method (2021) (1)
Accurate Prediction of BRCA 1 and BRCA 2 Heterozygous Genotype Using Expression Profiling after Induced DNADamage (2006) (1)
Embedded Ridge Approximations: Constructing Ridge Approximations Over Localized Scalar Fields For Improved Simulation-Centric Dimension Reduction (2019) (1)
Bayesian Assessments of Aeroengine Performance (2020) (1)
Discussion of the paper: “Sampling schemes for generalized linear Dirichlet process random effects models” by M. Kyung, J. Gill, and G. Casella (2011) (1)
Non‐parametric Bayes to infer playing strategies adopted in a population of mobile gamers (2015) (1)
$Φ$-DVAE: Learning Physically Interpretable Representations with Nonlinear Filtering (2022) (1)
Fahlman-Type Activation Functions Applied to Nonlinear PCA Networks Provide a Generalised Independent Component Analysis (1997) (1)
Preferential attachment of specific fluorescent dyes and dye labelled DNA sequences in a SERS multiplex (2016) (1)
A graph representation based on fluid diffusion model for multimodal data analysis: theoretical aspects and enhanced community detection (2021) (1)
de Probabilistic numerics and uncertainty in computations (2015) (1)
On the Use of Diagonal and Class-Dependent Weighted Distances for the Probabilistic k-Nearest Neighbor (2011) (1)
Discussion of "Sequential Quasi-Monte Carlo" by Mathieu Gerber and Nicolas Chopin (2015) (1)
Tracking Independent Sources (1997) (1)
Recasting the context in information retrieval (1996) (1)
Accelerated Whole-Core Analysis Optimization With Wellsite Tomography Instrumentation and Bayesian Inversion (2019) (0)
Pattern Classification with Gaussian Processes (2017) (0)
An unsupervised artificial neural network approach to adaptive noise cancellation applied to on-line tool condition monitoring (1998) (0)
Title Inferring Signaling Pathway Topologies from MultiplePerturbation Measurements of Specific Biochemical Species (2018) (0)
Bayesian inference for model selection: an application to aberrant signalling pathways in chronic myeloid leukaemia (2015) (0)
Two-level infinite mixture for multi-domain data (2008) (0)
Gracie, Kirsten and Moores, Matthew and Smith, W. Ewen and Harding, Kerry and Girolami, Mark and Graham, Duncan and Faulds, Karen (2016) Preferential attachment of specific fluorescent dyes and dye labeled dna sequences in a surface enhanced raman scattering (2019) (0)
THE THERMODYNAMICS OF URBAN AND REGIONAL STRUCTURE (2018) (0)
Chapter 1 Phylogenetic Gaussian Processes for Bat Echolocation (2018) (0)
A comparison of bacterial and human prolyl oligopeptidases: 3D-QSAR analysis of amino acid and thioxo amino acid pyrrolidides and thiazolidides as inhibitors of prolyl oligopeptidases and examination of the binding sites in the homology models of prolyl oligopeptidases (2002) (0)
A probabilistic model for quantifying uncertainty in the failure assessment diagram (2022) (0)
Solving Large-Scale PDE-constrained Bayesian Inverse Problems with RMHMC 2 Keywords Riemann manifold Hamiltonian (0)
Geometry & Dynamics for Markov Chain Monte Carlo (2021) (0)
Artificial Neural Networks and Machine Learning - Proceedings of ICANN 2011 - 21st International Conference on Artificial Neural Networks, Part I (2011) (0)
A graph representation based on fluid diffusion model for data analysis: theoretical aspects and enhanced community detection (2021) (0)
Bernoulli On the Geometric Ergodicity of Hamiltonian Monte (2018) (0)
Error analysis for a statistical finite element method (2022) (0)
An ICT-Enabled Approach to Optimising the Reliability of Manual Ultrasonic Non-Destructive Testing (2012) (0)
PR ] 6 M ay 2 02 1 A UNIFYING AND CANONICAL DESCRIPTION OF MEASURE-PRESERVING (2021) (0)
Employing Bayesian analysis in pathway modelling (Abstract only) (2006) (0)
Sobolev Spaces, Kernels and Discrepancies over Hyperspheres (2022) (0)
Topic Identification in Chat line Discussions by Extracting Independent Minimum Complexity Time Components (2002) (0)
Edinburgh Research Explorer The Grouped Author-Topic Model for Unsupervised Entity Resolution (2011) (0)
Information Theoretic Non-Linear Feature Extraction and Blind Source Separation (1999) (0)
University of Groningen The silicon trypanosome (2017) (0)
Statistical and probabilistic fundamentals of ICA (2004) (0)
Random Grid Neural Processes for Parametric Partial Differential Equations (2023) (0)
Markov Chain Monte Carlo Sampling (2016) (0)
Embedded Ridge Approximations4 (2020) (0)
Abstract 2104: Evidence for E2F/EWS-FLI1 oncoprotein synergism using systems biology (2015) (0)
Kernelized Variance Reduction for Quasi-Monte Carlo (2015) (0)
Proceedings of the Glasgow –strathclyde Information Retrieval Workshop Evaluating Interactive Information Retrieval in Simulated and Real Environment .......................... 9 (2004) (0)
Applied Probability by LANGE, K. (2012) (0)
Control functionals for Monte Carlo integration Series B Statistical methodology (2017) (0)
2 Riemannian Manifold Hamiltonian Monte Carlo (2012) (0)
Implementing Bayesian Methods for Ion Channel Modelling (2000) (0)
GMCMC: First release (2014) (0)
Chasing microns in an unconstrained manufacturing environment (1995) (0)
Regression Estimators: A Comparative Study by GRUBER, M. H. J. (2012) (0)
Principal Components Analysis and Latent Variable Models (2016) (0)
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation (2023) (0)
Reversible jump Riemann Manifold Hamiltonian Monte Carlo (2012) (0)
Bayesian Modelling of Raman Spectroscopy [R package serrsBayes version 0.4-1] (2020) (0)
The Pearson Mixture Model for Cluster Analysis and Data Visualisation (1998) (0)
Multivariate Density Factorisation for Independent Component Analysis : An Unsupervised Artificial Neural Network Approach (2021) (0)
Linear Modelling: A Maximum Likelihood Approach (2016) (0)
Linear Modelling: A Least Squares Approach (2016) (0)
A determinant‐free method to simulate the parameters of large Gaussian fields (2017) (0)
INSIGHTS INTO SALT-SENSITIVE HYPERTENSION USING RESPONSE-RELEVANT CLUSTERING: PP.21.317 (2010) (0)
The Non-Linear PCA Algorithm and Blind Source Separation (1999) (0)
Edinburgh Research Explorer Transformation Equivariant Boltzmann Machines (2018) (0)
Book and Media Review Editor (2008) (0)
Explorer Transformation Equivariant Boltzmann Machines (2011) (0)
Background to Blind Source Separation (1999) (0)
Editorial: special edition on probabilistic numerics (2019) (0)
Comparison of wideband LMS, subband LMS, and a nonlinear entropic neural approach to adaptive noise cancellation for speech enhancement (1999) (0)
Principal Components Identify MLP Hidden Layer Size for Optimal Generalisation Performance (1997) (0)
Burglary in London: insights from statistical heterogeneous spatial point processes (2019) (0)
Multi-fidelity approach to Bayesian parameter estimation in subsurface heat and fluid transport models (2021) (0)
A mixture modeling approach for clustering log files with coreset and user feedback (2022) (0)
A comparative evaluation of stochastic-based inference methods for Gaussian process models (2013) (0)
Inferring networks from time series: a neural approach (2023) (0)
Discussion of "Geodesic Monte Carlo on Embedded Manifolds" (2013) (0)
Non-Linear Feature Extraction and Blind Source Separation (1999) (0)

This paper list is powered by the following services:

Other Resources About Mark Girolami

What Schools Are Affiliated With Mark Girolami?

Mark Girolami is affiliated with the following schools: