Samuel Livingstone

Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions

Mark A. Girolami, Samuel Livingstone, M. Girolami, 2014, Entropy.

A fresh take on 'Barker dynamics' for MCMC.

Giacomo Zanella, Samuel Livingstone, Max Hird, 2020 .

The Barker proposal: combining robustness and efficiency in gradient-based MCMC

Giacomo Zanella, Samuel Livingstone, 2019 .

Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families

Arthur Gretton, Zoltán Szabó, Dino Sejdinovic, 2015, NIPS.

Optimal design of the Barker proposal and other locally-balanced Metropolis-Hastings algorithms

Giacomo Zanella, Jure Vogrinc, Samuel Livingstone, 2022 .

Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable Selection

Jim Griffin, Samuel Livingstone, Xitong Liang, 2021 .

Geometric Ergodicity of the Random Walk Metropolis with Position-Dependent Proposal Covariance

Samuel Livingstone, Samuel Livingstone, 2015 .