1 research outputs found
Loop corrections for message passing algorithms in continuous variable models
In this paper we derive the equations for Loop Corrected Belief Propagation
on a continuous variable Gaussian model. Using the exactness of the averages
for belief propagation for Gaussian models, a different way of obtaining the
covariances is found, based on Belief Propagation on cavity graphs. We discuss
the relation of this loop correction algorithm to Expectation Propagation
algorithms for the case in which the model is no longer Gaussian, but slightly
perturbed by nonlinear terms