The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Statistical methods for voice conversion are usually based on a single model selected in order to represent a tradeoff between goodness of fit and complexity. In this paper we ass...
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Fitting statistical 2D and 3D shape models to images is necessary for a variety of tasks, such as video editing and face recognition. Much progress has been made on local fitting...
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...