Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
Graphs are an extremely general and powerful data structure. In pattern recognition and computer vision, graphs are used to represent patterns to be recognized or classified. Det...
In this paper, we investigate the feasibility of using graph-based descriptions to learn the view structure of 3D objects. The graphs used in our study are constructed from the De...
Given a sequence of non-negative real numbers 0 1 ::: which sum to 1, we consider a random graph having approximately in vertices of degree i. In 12] the authors essentially show ...
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...