Previous work on sensitivity analysis in Bayesian networks has focused on single parameters, where the goal is to understand the sensitivity of queries to single parameter changes...
In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
Histograms are a very useful tool for data analysis, because they show the distribution of values over a data dimension. Many data sets in engineering (like computational fluid dy...
This paper presents an approach to collision detection and response for dynamically deforming pointbased objects. Both the volume of an object and its surface are represented by p...
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...