This paper has two goals. First, we develop frameworks for logical systems which are able to re ect not only nonmonotonic patterns of reasoning, but also paraconsistent reasoning....
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a...
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
The extraction and display of iso-surfaces is a standard method for the visualization of volume data sets. In this paper we present a novel approach that utilizes a hierarchy on b...
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...