Expectation propagation

Sat, 18 Jul 2026 09:57:25 +0000

Definition

Expectation Propagation (EP) approximates intractable integrals by iteratively refining Gaussian approximations to the true posterior distribution. It minimizes the Kullback-Leibler divergence between the approximate and true distributions by matching moments. EP is widely used in Bayesian machine learning for tasks like classification and regression where exact inference is computationally prohibitive, offering a balance between accuracy and efficiency.

Summary

An approximate inference algorithm used to estimate posterior distributions in complex probabilistic graphical models.

Bayesian Methods on English AI Terms Dictionary

Expectation propagation

Definition

Summary