We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
Blind source separation, which supposes that the sources are independent, is a well known domain in signal processing. However, in a noisy environment the estimation of the criteri...
Bertrand Rivet, Vincent Vigneron, Anisoara Parasch...
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
We present a new image restoration method based on modelling the coefficients of an overcomplete wavelet response to natural images with a mixture of two Gaussian distributions, h...
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...