2 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable Selection
Xitong Liang, Samuel Livingstone, Jim Griffin
We introduce a framework for efficient Markov Chain Monte Carlo (MCMC) algorithms targeting discrete-valued high-dimensional distributions, such as posterior distributions in Bayes…