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stat.ML2026
Steering Diffusion Models to Rare Events with Sequential Monte Carlo
Aavash Subedi, Tim Reichelt, Christopher Williams +3
Diffusion models are increasingly used as surrogates for expensive simulators in weather prediction, molecular dynamics, and materials design. In these models, computing the probab…
stat.ML2026
Metropolis-Adjusted Diffusion Models
Kevin H. Lam, Tyler Farghly, Christopher Williams +3
Sampling from score-based diffusion models incurs bias due to both time discretisation and the approximation of the score function. A common strategy for reducing this bias is to a…
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…