Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Background: The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy func...
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Abstract. Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmenta...
Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanath...
The concept of graph cuts is by now a standard method
for all sorts of low level vision problems. Its popularity is
largely due to the fact that globally or near globally optimal...
Carl Olsson, Martin Byr¨od, Niels Chr. Overgaard,...