In this paper we present an algorithm and software for generating arbitrarily large Bayesian Networks by tiling smaller real-world known networks. The algorithm preserves the stru...
Ioannis Tsamardinos, Alexander R. Statnikov, Laura...
Abstract. Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with ...
Johan Kwisthout, Hans L. Bodlaender, Linda C. van ...
—Ant colony optimization (ACO) is a probabilistic technique used for solving complex computational problems, such as finding optimal routes in networks. It has been proved to pe...
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
In robotic radiosurgery, a photon beam source, moved by a robot arm, is used to ablate tumors. The accuracy of the treatment can be improved by predicting respiratory motion to com...
Floris Ernst, Alexander Schlaefer, Achim Schweikar...