The cluster variation method (CVM) is a hierarchy of approximate variational techniques for
discrete (Ising-like) models in equilibrium statistical mechanics, improving on the mean-field …

A general framework for constructing and using probabilistic models of complex systems that
would enable a computer to use available information for making decisions. Most tasks …

The formalism of probabilistic graphical models provides a unifying framework for capturing
complex dependencies among random variables, and building large-scale multivariate …

Abstract Language is a social phenomenon and variation is inherent to its social nature.
Recently, there has been a surge of interest within the computational linguistics (CL) …

Tree-reweighted max-product message passing (TRW) is an algorithm for energy
minimization introduced recently by Wainwright et al.[7]. It shares some similarities with …

State-of-the-art research on MRFs, successful MRF applications, and advanced topics for
future study. This volume demonstrates the power of the Markov random field (MRF) in …

We reformulate a class of non-linear stochastic optimal control problems introduced by
Todorov (in Advances in Neural Information Processing Systems, vol. 19, pp. 1369–1376 …

Occlusion reasoning is a fundamental problem in computer vision. In this paper, we propose
an algorithm to recover the occlusion boundaries and depth ordering of free-standing …

We introduce a new class of upper bounds on the log partition function of a Markov random
field (MRF). This quantity plays an important role in various contexts, including …

This paper describes the software package libDAI, a free & open source C++ library that
provides implementations of various exact and approximate inference methods for graphical …