Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
—This paper proposes a probabilistic technique that enables a node to estimate the number of its neighbors that fulfill certain criteria. The technique does not require any a pr...
Helmut Adam, Evsen Yanmaz, Wilfried Elmenreich, Ch...
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
—We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specif...