We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 a...
Markov jump processes play an important role in a large number of application domains. However, realistic systems are analytically intractable and they have traditionally been ana...
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
The increasingly common practice of replicating datasets and using resources as distributed data stores in Grid environments has led to the problem of determining which replica ca...
The quantization based filtering method (see [13], [14]) is a grid based approximation method to solve nonlinear filtering problems with discrete time observations. It relies on o...