3 papers
stat.ML2026
Accelerated Parallel Tempering via Neural Transports
Leo Zhang, Peter Potaptchik, Jiajun He +5
Markov Chain Monte Carlo (MCMC) algorithms are essential tools in computational statistics for sampling from unnormalised probability distributions, but can be fragile when targeti…
stat.CO2025
Optimised Annealed Sequential Monte Carlo Samplers
Saifuddin Syed, Alexandre Bouchard-Côté, Kevin Chern +1
Annealed Sequential Monte Carlo (ASMC) samplers are special cases of SMC samplers where the sequence of distributions can be embedded in a smooth path of distributions. Using this…
stat.ML2024
Score-Optimal Diffusion Schedules
Christopher Williams, Andrew Campbell, Arnaud Doucet +1
Denoising diffusion models (DDMs) offer a flexible framework for sampling from high dimensional data distributions. DDMs generate a path of probability distributions interpolating…