Background: We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive app...
Svetlana Bulashevska, Alla Bulashevska, Roland Eil...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
This paper presents an approach to matching parts of deformable shapes. Multiscale salient parts of the two shapes are first identified. Then, these parts are matched if their im...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Extremely crowded scenes present unique challenges to
video analysis that cannot be addressed with conventional
approaches. We present a novel statistical framework for
modeling...
Louis Kratz (Drexel University), Ko Nishino (Drexe...