Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this...
A Knowledge Based Network is a type of ontological content based network. As Knowledge Based Networks scale, semantic interoperability becomes an important issue since larger popul...
Song Guo, John Keeney, Declan O'Sullivan, David Le...
Parameterizations of triangulated surfaces are used in an increasing number of mesh processing applications for various purposes. Although demands vary, they are often required to...