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This paper presents recent advances in the statistical modeling of random graphs that have an impact on the empirical study of social networks. Statistical exponential family models (Wasserman and Pattison 1996) are a generalization of the Markov random graph models introduced by Frank and Strauss (1986), which in turn are derived from developments in(More)
We address the problem of estimating the support domain of a bounded spatial point process in the presence of background noise. This happens for example when detecting a mineeeld from aerial observations. The image returned by the electronic device contains putative mine locations and is corrupted by clutter. The problem is to nd the boundaries of the(More)
We describe a probabilistic approach to simultaneous image segmentation and intensity estimation for complementary DNA microarray experiments. The approach overcomes several limitations of existing methods. In particular, it (a) uses a flexible Markov random field approach to segmentation that allows for a wider range of spot shapes than existing methods,(More)
and Critical Care for sharing the data in Figure 3 (a). Abstract We consider the problems of image segmentation and classiication, and image restoration when the true image is made up of a small number of (unordered) colors. Our emphasis is on both performance and speed; speed has become increasingly important for analyzing large images and multispectral(More)
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