140 citations · 1.9k across the 86 of their papers we have counts for
4 papers · 2 filters
Hamiltonian Monte Carlo for Hierarchical Models
M. J. Betancourt, Mark Girolami
Hierarchical modeling provides a framework for modeling the complex interactions typical of problems in applied statistics. By capturing these relationships, however, hierarchical…
Langevin diffusions and the Metropolis-adjusted Langevin algorithm
Tatiana Xifara, Chris Sherlock, Samuel Livingstone +2
We provide a clarification of the description of Langevin diffusions on Riemannian manifolds and of the measure underlying the invariant density. As a result we propose a new posit…
On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods
Anne-Marie Lyne, Mark Girolami, Yves Atchadé +2
A large number of statistical models are "doubly-intractable": the likelihood normalising term, which is a function of the model parameters, is intractable, as well as the marginal…
Bayesian Solution Uncertainty Quantification for Differential Equations
Oksana A. Chkrebtii, David A. Campbell, Ben Calderhead +1
We explore probability modelling of discretization uncertainty for system states defined implicitly by ordinary or partial differential equations. Accounting for this uncertainty c…