We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
Context-dependent word similarity can be measured over multiple cross-cutting dimensions. For example, lung and breath are similar thematically, while authoritative and superfici...
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
We introduce a generative probabilistic document model based on latent Dirichlet allocation (LDA), to deal with textual errors in the document collection. Our model is inspired by...
Abstract. This paper proposes a statistical model of functional landmarks delimiting low level visual areas which are highly variable across individuals. Low level visual areas are...
Isabelle Corouge, Michel Dojat, Christian Barillot