Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
We describe here our ongoing research on modeling conceptual and narrative structure of fairytales by a computer system. In this paper we focus on the variations of fairytales base...
Markov Logic Networks (MLNs) combine Markov Networks and first-order logic by attaching weights to firstorder formulas and viewing them as templates for features of Markov Networks...
In this paper we present a method for flexible protein structure alignment based on elastic shape analysis of backbones, in a manner that can incorporate different characteristics...
This paper describes a framework for the estimation of shape from sparse or incomplete range data. It uses a shape representation called blending, which allows for the geometric c...