Explaining away has mostly been considered in terms of inference of states in belief networks. We show how it can also arise in a Bayesian context in inference about the weights g...
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
In this paper, we propose a new stochastic language model that integrates local and global constraints effectively and describe a speechrecognition system basedon it. Theproposedl...
Understanding the hierarchical relationships among biochemical, metabolic, and physiological systems in the mapping between genotype and phenotype is expected to improve the diagno...
This paper explores how to exploit shape information to perform object class recognition. We use a sparse partbased model to describe object categories defined by shape. The spars...
Josephine Sullivan, Oscar M. Danielsson, Stefan Ca...