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20212026
most citedA Note on the Polynomial Ergodicity of the One-Dimensional Zig-Zag process

1 citations · 1 across the 7 of their papers we have counts for

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7 papers

math.NA2026

Pathwise skew-symmetric discretisation for SDEs with superlinear drift

Yuga Iguchi, Samuel Livingstone, Giorgos Vasdekis +1

The skew-symmetric discretisation has recently been proposed as a new robust simulation method for weakly approximating stochastic differential equations (SDEs) with non-globally L…

stat.CO2025

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…

math.PR2025

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…

stat.CO2025

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…

math.PR2024

Skew-symmetric schemes for stochastic differential equations with non-Lipschitz drift: an unadjusted Barker algorithm

Yuga Iguchi, Samuel Livingstone, Nikolas Nüsken +2

We propose a new simple and explicit numerical scheme for time-homogeneous stochastic differential equations. The scheme is based on sampling increments at each time step from a sk…

math.PR2021★ 1 cited

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…

math.PR2021

Speed Up Zig-Zag

Giorgos Vasdekis, Gareth O. Roberts

Zig-Zag is Piecewise Deterministic Markov Process, efficiently used for simulation in an MCMC setting. As we show in this article, it fails to be exponentially ergodic on heavy tai…