We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
We introduce a graphical framework for Bayesian inference that is sufficiently general to accommodate not just the standard case but also recent proposals for a theory of quantum...
— Intention recognition is an important topic in human-robot cooperation that can be tackled using probabilistic model-based methods. A popular instance of such methods are Bayes...
Oliver C. Schrempf, David Albrecht, Uwe D. Hanebec...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Automatic audio classification usually considers sounds as music, speech, silence or noise, but works about the noise class are rare. Audio features are generally specific to sp...
Pierre Hanna, Nicolas Louis, Myriam Desainte-Cathe...