Expectation propagation

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search

Expectation propagation (EP) is a technique in Bayesian machine learning.

EP finds approximations to a probability distribution. It uses an iterative approach that leverages the factorization structure of the target distribution. It differs from other Bayesian approximation approaches such as Variational Bayesian methods.


External links[edit]