Research in temporal databases has mainly focused on defining temporal data models by extending existing models, and developing access structures for temporal data. Little has bee...
In real life, visual learning is supposed to be a continuous process. Humans have an innate facility to recognize objects even under less-than-ideal conditions and to build robust ...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Current visualization systems are typically based on the concept of interactive post-processing. This decoupling of data visualization from the process of data generation offers a...
Recently a class of multiscale stochastic models has been introducedin which Gaussian random processes are described by scale-recursive dynamics that are indexed by the nodes of a...
Paul W. Fieguth, William W. Irving, Alan S. Willsk...