We present a software package for the simulation of very large neuronal networks on parallel computers. The package can be run on any system with an implementation of the Message ...
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
This paper presents a case study of using simulation for analyzing the impact of proposed changes in the supply chain processes for a large logistics operation. The major changes ...
Sanjay Jain, Eric C. Ervin, Andrew P. Lathrop, Rus...
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification ...