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stat.ML2026
Tempered Guided Diffusion
Andreas Makris, Paul Fearnhead, Chris Nemeth
Training-free conditional diffusion provides a flexible alternative to task-specific conditional model training, but existing samplers often allocate computation inefficiently: ind…
stat.ML2026
Scalable Model-Based Clustering with Sequential Monte Carlo
Connie Trojan, Pavel Myshkov, Paul Fearnhead +3
In online clustering problems, there is often a large amount of uncertainty over possible cluster assignments that cannot be resolved until more data are observed. This difficulty…
stat.ML2024
Scalable Monte Carlo for Bayesian Learning
Paul Fearnhead, Christopher Nemeth, Chris J. Oates +1
This book aims to provide a graduate-level introduction to advanced topics in Markov chain Monte Carlo (MCMC) algorithms, as applied broadly in the Bayesian computational context.…