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08/01/2023
Adaptive MCMC for Bayesian variable selection in generalised linear models and survival models
Developing an efficient computational scheme for high-dimensional Bayesi...
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08/09/2022
Sampling algorithms in statistical physics: a guide for statistics and machine learning
We discuss several algorithms for sampling from unnormalized probability...
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06/28/2022
A Bayesian hierarchical model for improving exercise rehabilitation in mechanically ventilated ICU patients
Patients who are mechanically ventilated in the intensive care unit (ICU...
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01/04/2022
Optimal design of the Barker proposal and other locally-balanced Metropolis-Hastings algorithms
We study the class of first-order locally-balanced Metropolis–Hastings a...
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10/22/2021
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable Selection
We introduce a framework for efficient Markov Chain Monte Carlo (MCMC) a...
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12/17/2020
A fresh take on 'Barker dynamics' for MCMC
We study a recently introduced gradient-based Markov chain Monte Carlo m...
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08/30/2019
On the robustness of gradient-based MCMC algorithms
We analyse the tension between robustness and efficiency for Markov chai...
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06/14/2019
Peskun-Tierney ordering for Markov chain and process Monte Carlo: beyond the reversible scenario
Historically time-reversibility of the transitions or processes underpin...
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01/29/2016
On the Geometric Ergodicity of Hamiltonian Monte Carlo
We establish general conditions under which Markov chains produced by th...
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06/08/2015