756 citations · 3.9k across the 84 of their papers we have counts for
25 papers · 1 filter
Scaling of Piecewise Deterministic Monte Carlo for Anisotropic Targets
Joris Bierkens, Kengo Kamatani, Gareth O. Roberts
Piecewise deterministic Markov processes (PDMPs) are a type of continuous-time Markov process that combine deterministic flows with jumps. Recently, PDMPs have garnered attention w…
Annealed Leap-Point Sampler for Multimodal Target Distributions
Nicholas G. Tawn, Matthew T. Moores, Hugo Queniat +1
In Bayesian statistics, exploring high-dimensional multimodal posterior distributions poses major challenges for existing MCMC approaches. This paper introduces the Annealed Leap-P…
Divide-and-Conquer Fusion
Ryan S. Y. Chan, Murray Pollock, Adam M. Johansen +1
Combining several (sample approximations of) distributions, which we term sub-posteriors, into a single distribution proportional to their product, is a common challenge. Occurring…
Flexible Bayesian inference for diffusion processes using splines
Paul A. Jenkins, Murray Pollock, Gareth O. Roberts
We introduce a flexible method to simultaneously infer both the drift and volatility functions of a discretely observed scalar diffusion. We introduce spline bases to represent the…
Dimension-free Mixing for High-dimensional Bayesian Variable Selection
Quan Zhou, Jun Yang, Dootika Vats +2
Yang et al. (2016) proved that the symmetric random walk Metropolis--Hastings algorithm for Bayesian variable selection is rapidly mixing under mild high-dimensional assumptions. W…
Bayesian Fusion: Scalable unification of distributed statistical analyses
Hongsheng Dai, Murray Pollock, Gareth Roberts
There has recently been considerable interest in addressing the problem of unifying distributed statistical analyses into a single coherent inference. This problem naturally arises…