Abstract-- This paper introduces a global uncertainty propagation scheme for the attitude dynamics of a rigid body, through a combination of numerical parametric uncertainty techni...
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
This paper considers the problem of knowledgebased model construction in the presence of uncertainty about the association of domain entities to random variables. Multi-entity Bay...
When dealing with ill-posed inverse problems in data analysis, the Bayesian approach allows one to use prior information to guide the result toward reasonable solutions. In this w...
K. M. Hanson, G. S. Cunningham, G. R. Jennings Jr....
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...