Combinatorial inference for graphical models
نویسندگان
چکیده
منابع مشابه
Heron Inference for Bayesian Graphical Models
Bayesian graphical models have been shown to be a powerful tool for discovering uncertainty and causal structure from real-world data in many application fields. Current inference methods primarily follow different kinds of trade-offs between computational complexity and predictive accuracy. At one end of the spectrum, variational inference approaches perform well in computational efficiency, w...
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So far we have seen two graphical models that are used for inference the Bayesian network and the Join tree. These two both represent the same joint probability distribution, but in different ways. Both express local properties which are used to make the inference computations tractable. The Bayesian net has the desirable property that it expresses a causal relationship between the variables wh...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2019
ISSN: 0090-5364
DOI: 10.1214/17-aos1650