33 citations · 34 across the 5 of their papers we have counts for
5 papers
Averaging polyhazard models using Piecewise deterministic Monte Carlo with applications to data with long-term survivors
Luke Hardcastle, Samuel Livingstone, Gianluca Baio
Polyhazard models are a class of flexible parametric models for modelling survival over extended time horizons. Their additive hazard structure allows for flexible, non-proportiona…
Structure Learning with Adaptive Random Neighborhood Informed MCMC
Alberto Caron, Xitong Liang, Samuel Livingstone +1
In this paper, we introduce a novel MCMC sampler, PARNI-DAG, for a fully-Bayesian approach to the problem of structure learning under observational data. Under the assumption of ca…
Adaptive MCMC for Bayesian variable selection in generalised linear models and survival models
Xitong Liang, Samuel Livingstone, Jim Griffin
Developing an efficient computational scheme for high-dimensional Bayesian variable selection in generalised linear models and survival models has always been a challenging problem…
A Bayesian hierarchical model for improving exercise rehabilitation in mechanically ventilated ICU patients
Luke Hardcastle, Samuel Livingstone, Claire Black +2
Patients who are mechanically ventilated in the intensive care unit (ICU) participate in exercise as a component of their rehabilitation to ameliorate the long-term impact of criti…
The Geometric Foundations of Hamiltonian Monte Carlo
M. J. Betancourt, Simon Byrne, Samuel Livingstone +1
Although Hamiltonian Monte Carlo has proven an empirical success, the lack of a rigorous theoretical understanding of the algorithm has in many ways impeded both principled develop…