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...
Estimating the variance of the sample mean from a stochastic process is essential in assessing the quality of using the sample mean to estimate the population mean which is the fu...
In this paper we present a new method to estimate optical flow for large displacements. It is based on prediction of global flow field parameters, performs better than multiresolu...
A posteriori error estimates are derived for unsteady convection-diffusion equations discretized with the non-symmetric interior penalty and the local discontinuous Galerkin metho...
We present two methods for estimating replacement probabilities without using parallel corpora. The first method proposed exploits the possible translation probabilities latent in ...