Annealed Importance Sampling with q-Paths

Code

• github.com/vmasrani/q_paths
  OfficialIn papernone★ 0
• github.com/shgoshtasb/cr_ais
  pytorch★ 1

Abstract

Annealed importance sampling (AIS) is the gold standard for estimating partition functions or marginal likelihoods, corresponding to importance sampling over a path of distributions between a tractable base and an unnormalized target. While AIS yields an unbiased estimator for any path, existing literature has been primarily limited to the geometric mixture or moment-averaged paths associated with the exponential family and KL divergence. We explore AIS using q-paths, which include the geometric path as a special case and are related to the homogeneous power mean, deformed exponential family, and -divergence.

Reproductions