In this paper, we propose a Bayesian model and a Monte Carlo Markov chain (MCMC) algorithm for reconstructing images that consist of only few non-zero pixels. An appropriate distr...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...
We investigate explicit segment duration models in addressing the problem of fragmentation in musical audio segmentation. The resulting probabilistic models are optimised using Mar...
Samer A. Abdallah, Mark B. Sandler, Christophe Rho...
In this paper, models and algorithms are presented for transcription of pitch and timings in polyphonic music extracts, focusing on the algorithm details of the sequential Markov ...
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...