15 citations · 15 across the 5 of their papers we have counts for
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stat.CO2026
From Continuous Dynamics to Practical Gradient-Based Samplers
James Chok
Gradient-based Markov chain Monte Carlo methods are often introduced as a catalog of algorithms: Hamiltonian Monte Carlo (HMC), the Metropolis-adjusted Langevin algorithm (MALA), t…
stat.CO2025
Constrained Dikin-Langevin diffusion for polyhedra
James Chok, Domenic Petzinna
We propose a reflection-free Langevin framework for sampling and optimization on compact polyhedra. The method is based on the inverse Hessian of the logarithmic barrier, which def…
stat.CO2025
Divide, Interact, Sample: The Two-System Paradigm
James Chok, Myung Won Lee, Daniel Paulin +1
Mean-field, ensemble-chain, and adaptive samplers have historically been viewed as distinct approaches to Monte Carlo sampling. In this paper, we present a unifying {two-system} fr…