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Graphical Modelling and Hierarchical Models

2021
In many contexts, straightforward exchangeability can be a useful simplifying assumption for specifying the joint probability distribution of random variables. But sometimes an individual will require more complex structures of statistical dependence between random quantities to properly represent their beliefs.
openaire   +2 more sources

Graphical Modeling

2013
This chapter is an introduction to the graphical approach for model generation. The concepts of “models” and “effects” are introduced. A tutorial approach is used to demonstrate how models can be created, tested, and simulated. The graphical approach to model abstraction is compared to a language-oriented approach and shown to be simpler and easier to ...
Peter R. Wilson, H. Alan Mantooth
openaire   +2 more sources

Multi-language evaluation of exact solvers in graphical model discrete optimization

Constraints, 2016
B. Hurley   +6 more
semanticscholar   +1 more source

The stitched puppet: A graphical model of 3D human shape and pose

Computer Vision and Pattern Recognition, 2015
S. Zuffi, Michael J. Black
semanticscholar   +1 more source

Graphical Models

2010
Dean K. Frederick   +2 more
openaire   +1 more source

An Introduction to Probabilistic Graphical Models

2002
In this chapter we will introduce two probabilistic graphical models -Bayesian networks and Gaussian networks- that will be used to carryout factorization of the probability distribution of the selected individuals in the Estimation of Distribution Algorithms based approaches.
openaire   +3 more sources

Graphical Models

2011
Julian McAuley   +2 more
openaire   +1 more source

Superpixel-Based Graphical Model for Remote Sensing Image Mapping

IEEE Transactions on Geoscience and Remote Sensing, 2015
Guangyun Zhang, X. Jia, Jiankun Hu
semanticscholar   +1 more source

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