In this paper, we study the problem of social relational inference using visual concepts which serve as indicators of actors’ social interactions. While social network analysis ...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transfor...
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindn...
We study the problemof statisticallycorrect inference in networks whose basic representations are population codes. Population codes are ubiquitous in the brain, and involve the s...
—We consider an end-to-end approach of inferring probabilistic data-forwarding failures in an externally managed overlay network, where overlay nodes are independently operated b...