The Belief Propagation algorithm is a popular technique of solving inference problems for different graph-like structures. We present a discussion of the dynamics of that algorithm for the Ising model on the square lattice. Our main goal was to describe limit fixed points for that algorithm, which are strictly connected with the marginal probabilities and stationary points of the Bethe Free Energy. Analytical considerations provide an exact analysis of a class of symmetrical points while numerical simulations confirm that for small lattices there are no non-symmetrical points. Notwithstanding the prevalent use of the Belief Propagation as an inference tool we present a sociophysical interpretation of its dynamics. In that case our considera...
Previously, we have considered belief propagation (BP) as a way to compute inference for a graph mod...
We study the performance of different message passing algorithms in the two-dimensional Edwards-Ande...
AbstractA new approximation of the cluster variational method is introduced for the three-dimensiona...
The Belief Propagation algorithm is a popular technique of solving inference problems for different ...
We first present an empirical study of the Belief Propagation (BP) algorithm, when run on the random...
Belief propagation (BP) was only supposed to work for tree-like networks but works surprisingly well...
Systems and control theory have found wide application in the analysis and design of numerical algor...
An important part of problems in statistical physics and computer science can be expressed as the co...
Important inference problems in statistical physics, computer vision, error-correcting coding theory...
Belief propagation (BP) is a message-passing method for solving probabilistic graphical models. It i...
The research reported in this thesis focuses on approximation techniques for inference in graphical ...
International audienceA number of problems in statistical physics and computer science can be expres...
We consider loopy belief propagation for approximate inference in probabilistic graphical models. A ...
Abstract. The cluster variation method has been developed into a general theoretical framework for t...
We continue our numerical study of quantum belief propagation initiated in [Phys. Rev. A 77, 052318 ...
Previously, we have considered belief propagation (BP) as a way to compute inference for a graph mod...
We study the performance of different message passing algorithms in the two-dimensional Edwards-Ande...
AbstractA new approximation of the cluster variational method is introduced for the three-dimensiona...
The Belief Propagation algorithm is a popular technique of solving inference problems for different ...
We first present an empirical study of the Belief Propagation (BP) algorithm, when run on the random...
Belief propagation (BP) was only supposed to work for tree-like networks but works surprisingly well...
Systems and control theory have found wide application in the analysis and design of numerical algor...
An important part of problems in statistical physics and computer science can be expressed as the co...
Important inference problems in statistical physics, computer vision, error-correcting coding theory...
Belief propagation (BP) is a message-passing method for solving probabilistic graphical models. It i...
The research reported in this thesis focuses on approximation techniques for inference in graphical ...
International audienceA number of problems in statistical physics and computer science can be expres...
We consider loopy belief propagation for approximate inference in probabilistic graphical models. A ...
Abstract. The cluster variation method has been developed into a general theoretical framework for t...
We continue our numerical study of quantum belief propagation initiated in [Phys. Rev. A 77, 052318 ...
Previously, we have considered belief propagation (BP) as a way to compute inference for a graph mod...
We study the performance of different message passing algorithms in the two-dimensional Edwards-Ande...
AbstractA new approximation of the cluster variational method is introduced for the three-dimensiona...