Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
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...
Building models of the structure in musical signals raises the question of how to evaluate and compare different modeling approaches. One possibility is to use the model to impute...
Thierry Bertin-Mahieux, Graham Grindlay, Ron J. We...