140 citations · 1.9k across the 86 of their papers we have counts for
4 papers · 1 filter
MCMC inference for Markov Jump Processes via the Linear Noise Approximation
Vassilios Stathopoulos, Mark A. Girolami
Bayesian analysis for Markov jump processes is a non-trivial and challenging problem. Although exact inference is theoretically possible, it is computationally demanding thus its a…
Lagrangian Dynamical Monte Carlo
Shiwei Lan, Vassilios Stathopoulos, Babak Shahbaba +1
Hamiltonian Monte Carlo (HMC) improves the computational efficiency of the Metropolis algorithm by reducing its random walk behavior. Riemannian Manifold HMC (RMHMC) further improv…
A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices
Mingjun Zhong, Mark Girolami
We present a Bayesian scheme for the approximate diagonalisation of several square matrices which are not necessarily symmetric. A Gibbs sampler is derived to simulate samples of t…
Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation"
Christophe Andrieu, Simon Barthelme, Nicolas Chopin +11
This report is a collection of comments on the Read Paper of Fearnhead and Prangle (2011), to appear in the Journal of the Royal Statistical Society Series B, along with a reply fr…