Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
A new, practical, and efficient approach is proposed for 3D vascular segmentation and bifurcation structure extraction. The method uses a combination of mathematical morphology, re...
Yoshitaka Masutani, Thomas Schiemann, Karl Heinz H...
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Background: Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolution...