Message-passing method
Encyclopedia
Message-passing methods are a set of algorithms in statistics
/machine learning
for doing inference through local computation. Belief propagation
on Bayesian networks is a good example of a message-passing method.
Statistics
Statistics is the study of the collection, organization, analysis, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments....
/machine learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...
for doing inference through local computation. Belief propagation
Belief propagation
Belief propagation is a message passing algorithm for performing inference on graphical models, such as Bayesian networks and Markov random fields. It calculates the marginal distribution for each unobserved node, conditional on any observed nodes...
on Bayesian networks is a good example of a message-passing method.
- Variational message passingVariational message passingVariational message passing is an approximate inference technique for continuous- or discrete-valued Bayesian networks, with conjugate-exponential parents, developed by John Winn...
- Expectation propagationExpectation propagationExpectation propagation is a technique in Bayesian machine learning, developed by Thomas Minka.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...
- Junction tree algorithm