Spatio-temporal uncertainty is a special feature of moving objects due to the inability of precisely capturing or predicting their continuously changing locations. Indeterminate lo...
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and t...
Orion is a state-of-the-art uncertain database management system that extends the relational model to include probabilistic uncertain data as first call data types. This demonstra...
Sarvjeet Singh, Chris Mayfield, Sagar Mittal, Suni...
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...