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06/26/2023
Exploring the big data paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS)
Selection bias poses a challenge to statistical inference validity in no...
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06/05/2023
StabJGL: a stability approach to sparsity and similarity selection in multiple network reconstruction
In recent years, network models have gained prominence for their ability...
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03/01/2023
Bayesian outcome-guided multi-view mixture models with applications in molecular precision medicine
Clustering is commonly performed as an initial analysis step for uncover...
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12/15/2022
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
Recent work has reported that AI classifiers trained on audio recordings...
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12/15/2022
A large-scale and PCR-referenced vocal audio dataset for COVID-19
The UK COVID-19 Vocal Audio Dataset is designed for the training and eva...
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06/23/2022
Scalable Multiple Network Inference with the Joint Graphical Horseshoe
Network models are useful tools for modelling complex associations. If a...
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04/02/2022
Structural randomised selection
An important problem in the analysis of high-dimensional omics data is t...
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01/03/2022
On randomized sketching algorithms and the Tracy-Widom law
There is an increasing body of work exploring the integration of random ...
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11/08/2021
Bayesian profile regression for clustering analysis involving a longitudinal response and explanatory variables
The identification of sets of co-regulated genes that share a common fun...
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09/28/2021
Interoperability of statistical models in pandemic preparedness: principles and reality
We present "interoperability" as a guiding framework for statistical mod...
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04/28/2021
BayesSUR: An R package for high-dimensional multivariate Bayesian variable and covariance selection in linear regression
In molecular biology, advances in high-throughput technologies have made...
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03/02/2021
The `how' matters: A simulation-based assessment of the potential contributions of LFD tests for school reopening in England
During Covid-19 outbreaks, school closures are employed as part of gover...
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09/27/2020
Kernel learning approaches for summarising and combining posterior similarity matrices
When using Markov chain Monte Carlo (MCMC) algorithms to perform inferen...
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10/10/2019
Distributed Bayesian Computation for Model Choice
We propose a general method for distributed Bayesian model choice, where...
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10/10/2019
Distributed Computation for Marginal Likelihood based Model Choice
We propose a general method for distributed Bayesian model choice, using...
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11/08/2018
A global-local approach for detecting hotspots in multiple-response regression
We tackle modelling and inference for variable selection in regression p...
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09/21/2018
Shrinkage estimation of large covariance matrices using multiple shrinkage targets
Linear shrinkage estimators of a covariance matrix --- defined by a weig...
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08/02/2018
High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
Penalized likelihood methods are widely used for high-dimensional regres...
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03/21/2018