Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Background: A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA) has proven especial...
Roland Schwarz, Patrick Musch, Axel von Kamp, Bern...
A standard approach to large network visualization is to provide an overview of the network and a detailed view of a small component of the graph centred around a focal node. The u...
Tim Dwyer, Kim Marriott, Falk Schreiber, Peter J. ...
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...