This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
The protein folding problem consists of predicting the functional (native) structure of the protein given its linear sequence of amino acids. Despite extensive progress made in un...
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
We consider the problem of the exact simulation of random variables Z that satisfy the distributional identity Z L = V Y + (1 − V )Z, where V ∈ [0, 1] and Y are independent, an...