C. Furtlehner, J. Lasgouttes, A. De, and L. Fortelle, A Belief Propagation Approach to Traffic Prediction using Probe Vehicles, 2007 IEEE Intelligent Transportation Systems Conference, pp.1022-1027, 2007.
DOI : 10.1109/ITSC.2007.4357716

URL : https://hal.archives-ouvertes.fr/hal-00175627

T. Heskes, M. Opper, W. Wiegerinck, O. Winther, and O. Zoeter, Approximate inference techniques with expectation constraints, Journal of Statistical Mechanics: Theory and Experiment, vol.2005, issue.11, p.11015, 2005.
DOI : 10.1088/1742-5468/2005/11/P11015

T. M. Cover and J. A. Thomas, Elements of Information Theory, 2006.

F. R. Kschischang, B. J. Frey, and H. A. Loeliger, Factor graphs and the sum-product algorithm, IEEE Transactions on Information Theory, vol.47, issue.2, pp.498-519, 2001.
DOI : 10.1109/18.910572

M. Welling and Y. W. Teh, Approximate inference in Boltzmann machines, Artificial Intelligence, vol.143, issue.1, pp.19-50, 2003.
DOI : 10.1016/S0004-3702(02)00361-2

H. A. Bethe, Statistical Theory of Superlattices, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.150, issue.871, pp.552-575, 1935.
DOI : 10.1098/rspa.1935.0122

J. Pearl, Probabilistic Reasoning in Intelligent Systems: Network of Plausible Inference, 1988.

J. S. Yedidia, W. T. Freeman, and Y. Weiss, Generalized belief propagation, Advances in Neural Information Processing Systems, pp.689-695, 2001.

T. Heskes, Stable fixed points of loopy belief propagation are minima of the Bethe free energy, Advances in Neural Information Processing Systems, 2003.

S. Tatikonda and M. Jordan, Loopy belief propagation and Gibbs measures, Proc. of the 18th An. Conf. on Uncertainty in Art. Intel. (UAI-02), pp.493-50, 2002.

J. M. Mooij and H. J. Kappen, Sufficient Conditions for Convergence of the Sum–Product Algorithm, IEEE Transactions on Information Theory, vol.53, issue.12, pp.4422-4437, 2007.
DOI : 10.1109/TIT.2007.909166

A. T. Ihler, J. W. Fischer, I. , and A. S. Willsky, Loopy belief propagation: convergence and effects of message errors, J. Mach. Learn. Res, vol.6, pp.905-936, 2005.

M. J. Wainwright, Estimating the " wrong " graphical model: benefits in the computation-limited setting, JMLR, vol.7, pp.1829-1859, 2006.

M. J. Wainwright, Stochastic processes on graphs with cycles: geometric and variational approaches, 2002.

M. J. Wainwright, T. S. Jaakkola, and A. S. Willsky, Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudomoment matching, Workshop on Artificial Intelligence and Statistics, 2003.

W. Wiegerinck and T. Heskes, Fractional belief propagation, Advances in Neural Information Processing Systems 15, pp.438-445, 2003.

Y. Kabashima and D. Saad, TAP for decoding corrupted messages, Europhysics Letters (EPL), vol.44, issue.5, p.668, 1998.
DOI : 10.1209/epl/i1998-00524-7

J. J. Hopfield, Neural network and physical systems with emergent collective computational abilities, Proc. of Natl. Acad. Sci. USA, pp.2554-2558, 1982.

M. Mézard, G. Parisi, and M. A. Virasoro, Spin Glass Theory and Beyond, World Scientific, 1987.

D. J. Amit, H. Gutfreund, and H. Sompolinsky, Statistical mechanics of neural networks near saturation, Annals of Physics, vol.173, issue.1, pp.30-67, 1987.
DOI : 10.1016/0003-4916(87)90092-3

M. Talagrand, Rigorous results for the Hopfield model with many patterns, Probability Theory and Related Fields, vol.110, issue.2, pp.177-276, 1998.
DOI : 10.1007/s004400050148

D. J. Amit, H. Gutfreund, and H. Sompolinsky, Spin-glass models of neural networks, Physical Review A, vol.32, issue.2, pp.1007-1018, 1985.
DOI : 10.1103/PhysRevA.32.1007

N. Hansen and A. Ostermeier, Completely Derandomized Self-Adaptation in Evolution Strategies, Evolutionary Computation, vol.9, issue.2, pp.159-195, 2001.
DOI : 10.1016/0004-3702(95)00124-7

G. Grimmet, Discrete spatial and physical processes in probability, 2008.

J. S. Yedidia, W. T. Freeman, and Y. Weiss, Constructing Free-Energy Approximations and Generalized Belief Propagation Algorithms, IEEE Transactions on Information Theory, vol.51, issue.7, pp.2282-2312, 2005.
DOI : 10.1109/TIT.2005.850085

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

Y. Weiss, C. Yanover, and T. Meltzer, MAP estimation, linear programming and belief propagation with convex free energies, Proc. of the 23th An. Conf. on Uncertainty in Art. Intel. (UAI-07), 2007.