gradient-based proposals 1hamiltonian monte carlo 1high-dimensional sampling 1mcmc scaling 1metropolis-hastings 1
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stat.CO2026
Optimal scaling of MCMC algorithms: the Hamiltonian approach
P. Dobson, J. M. Sanz-Serna, K. C. Zygalakis
The paper develops a general Hamiltonian‑based framework to analyze how Metropolis‑Hastings MCMC algorithms should be scaled as the dimensionality of the target distribution grows,…
stat.CO2026
Piecewise Deterministic Sampling for Constrained Distributions
Joël Tatang Demano, Paul Dobson, Konstantinos Zygalakis
In this paper, we propose a novel class of Piecewise Deterministic Markov Processes (PDMPs) that are designed to sample from probability distributions supported on a convex se…