Optimised Annealed Sequential Monte Carlo Samplers

Understand

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 underlying path and a performance model based on the variance of the normalising constant estimator, we systematically study dense-schedule limits.
• From our theory emerges a notion of global barrier, capturing the inherent complexity of normalising constant approximation under our performance model.
• We then turn the resulting approximations into surrogate objective functions of algorithm performance, using them to guide method development.