A central theme of computational vision research has been the realization that reliable estimation of local scene properties requires propagating measurements across the image. Ma...
Belief propagation is a popular global optimization technique for many computer vision problems. However, it requires extensive computation due to the iterative message passing op...
We consider the task of aggregating beliefs of several experts. We assume that these beliefs are represented as probability distributions. We argue that the evaluation of any aggr...
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...