We present the development and use of a novel distributed geohazard modeling environment for the analysis and interpretation of large scale earthquake data sets. Our work demonstr...
Background: Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For examp...
Erwin P. Gianchandani, Matthew A. Oberhardt, Antho...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similar in spirit to existing grid and HPC ...
Daniel Nurmi, Richard Wolski, Chris Grzegorczyk, G...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...