Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
We introduce the graphlet decomposition of a weighted network, which encodes a notion of social information based on social structure. We develop a scalable algorithm, which combi...
A maximal prime subgraph decomposition junction tree (MPD-JT) is a useful computational structure that facilitates lazy propagation in Bayesian networks (BNs). A graphical method ...