Ensemble-Based Annealed Importance Sampling

Understand

Sampling from a multimodal distribution is a fundamental and challenging problem in computational science and statistics.

• Among various approaches proposed for this task, one popular method is Annealed Importance Sampling (AIS).
• In this paper, we propose an ensemble-based version of AIS by combining it with population-based Monte Carlo methods to improve its efficiency.
• By keeping track of an ensemble instead of a single particle along some continuation path between the starting distribution and the target distribution, we take advantage of the interaction within the ensemble to encourage the exploration of undiscovered modes.