Complex objects can often be conveniently represented by finite sets of simpler components, such as images by sets of patches or texts by bags of words. We study the class of posi...
Forecasting is of prime importance for accuracy in decision making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor ...
Rao–Blackwellization is an approximation technique for probabilistic inference that flexibly combines exact inference with sampling. It is useful in models where conditioning o...
Feature tracking algorithms for instationary vector fields are usually based on a correspondence analysis of the features at different time steps. This paper introduces a method ...
In this paper some initialwork towards a new approach to qualitative reasoning under uncertainty is presented. This method is not only applicable to qualitative probabilistic reas...