1 citations · 1 across the 3 of their papers we have counts for
4 papers
Some aspects of robustness in modern Markov Chain Monte Carlo
Sam Power, Giorgos Vasdekis
Markov Chain Monte Carlo (MCMC) is a flexible approach to approximate sampling from intractable probability distributions, with a rich theoretical foundation and comprising a wealt…
Foundations of locally-balanced Markov processes
Samuel Livingstone, Giorgos Vasdekis, Giacomo Zanella
We formally introduce and study locally-balanced Markov jump processes (LBMJPs) defined on a general state space. These continuous-time stochastic processes with a user-specified l…
Sampling with time-changed Markov processes
Andrea Bertazzi, Giorgos Vasdekis
We study time-changed Markov processes to speed up the convergence of Markov chain Monte Carlo (MCMC) algorithms. The time-changed process is defined by adjusting the speed of time…
A Note on the Polynomial Ergodicity of the One-Dimensional Zig-Zag process
G. Vasdekis, G. O. Roberts
We prove polynomial ergodicity for the one-dimensional Zig-Zag process on heavy tailed targets and identify the exact order of polynomial convergence of the process when targeting…