A Note on Gibbs Sampler and Coordinate Ascent Variational Inference

One of the fundamental problems in Bayesian statistics is the approximation of the posterior distribution. Gibbs sampler and coordinate ascent variational inference are renownedly utilized approximation techniques that rely on stochastic and deterministic approximations. This article aims to clarify the set-theoretical point of view on the two schemes and provide some insights for them.