Sharp dimensional analysis of midpoint methods for Langevin sampling
math.ST, cs.DS, cs.LG, cs.NA, math.NA, stat.TH
Submitted: 2026-10-05
Updated: 2026-10-05
Project page: https://chewisinho.github.io/main.pdf
Sources
- Smoothed Picard Hamiltonian Monte Carlo
- Exact simulation of diffusions and improved algorithms for log-concave sampling
- The shifted ODE method for underdamped Langevin MCMC
- Error bounds for Approximations of Markov chains used in Bayesian Sampling
- Mean square error analysis of stochastic gradient and variance-reduced sampling algorithms
- Theoretical guarantees for stochastic gradient sampling methods via Gaussian convolution inequalities
- Wasserstein mixing time of the unadjusted Langevin algorithm
- Analysis of Langevin midpoint methods using an anticipative Girsanov theorem
- Algorithmic warm starts for Hamiltonian Monte Carlo
- Sublinear iterations can suffice even for DDPMs
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