Computational Complexity Comparison via Scaling Limits for Emerging MCMC Samplers

Slide
PDMP
Author
Affiliation

Hirofumi Shiba

ISM (3rd year PhD Student)

Published

2/10/2026

概要

ISI-ISM-ISSAS Joint Conference, 2026. Slides are here. Preprint is here

1 What is a PDMP?

An illustration of a Piecewise Deterministic Markov Process. Output from the PDMPFlux.jl package.

1.1 Evolution of Monte Carlo

Markov Chain
(1953–)

Diffusion
(1978–)

PDMP
(2008–)

1.2 PDMP ≒ ODE + Jump

1.3 Which One is Faster ?

Zig-Zag Sampler
(Bierkens et al., 2019)

Bouncy Particle Sampler
(Bouchard-Côté et al., 2018)

Forward Event-Chain Monte Carlo
(Michel et al., 2020)

1.4 ESS Comparison

1.5 New Asymptotic Variance Estimator

References

Bierkens, J., Fearnhead, P., and Roberts, G. (2019). The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data. The Annals of Statistics, 47(3), 1288–1320.
Bouchard-Côté, A., Vollmer, S. J., and Doucet, A. (2018). The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method. Journal of the American Statistical Association, 113(522), 855–867.
Michel, M., Durmus, A., and Sénécal, S. (2020). Forward event-chain monte carlo: Fast sampling by randomness control in irreversible markov chains. Journal of Computational and Graphical Statistics, 29(4), 689–702.