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 ...
Abstract. We develop a differential geometric framework for regularizing diffusion MRI data. The key idea is to model white matter fibers as 3D space curves and to then extend Pare...
Peter Savadjiev, Jennifer S. W. Campbell, G. Bruce...
Abstract- In this paper we address the problem of finding valid solutions for the problem of inferring gene regulatory networks. Different approaches to directly infer the depende...
Christian Spieth, Felix Streichert, Nora Speer, An...
Abstract. In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. We introduce enhancements to an Evolutionary Algorithm op...
Christian Spieth, Felix Streichert, Nora Speer, An...
Abstract. Datatypes which differ inessentially in their names and structure are said to be isomorphic; for example, a ternary product is isomorphic to a nested pair of binary prod...