We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
We present an approach to teach incrementally human gestures to a humanoid robot. The learning process consists of first projecting the movement data in a latent space and encodin...
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...
The coordination language Paradigm allows for a flexible and orthogonal modeling of interprocess relationships at the architectural level. It is shown how dynamic system adaptation...
In a previous work, we developed a quasi-efficient maximum likelihood approach for blindly separating stationary, temporally correlated sources modeled by Markov processes. In this...