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Nonparametric Belief Propagation

By Erik B. Sudderth, Alexander T. Ihler, Michael Isard, William T. Freeman, Alan S. Willsky

Communications of the ACM, Vol. 53 No. 10, Pages 95-103

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Probabilistic graphical models and algorithms for approximate inference have proven to be powerful tools in a wide range of applications in statistics and AI. However, applying these methods to models with continuous variables remains a challenging task.

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