The Dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. The set of parameters o...
In this paper, we advocate decentralised process modelling and suggest that understanding and modelling the development processes of individual development participants is the key ...
Bashar Nuseibeh, Jeff Kramer, Anthony Finkelstein,...
We review the use of bond graphs for modeling of physico-chemical processes. We recall that bond graphs define a circuit-type language which root on a thermodynamical consistent d...
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
We propose a new hierarchical Bayesian n-gram model of natural languages. Our model makes use of a generalization of the commonly used Dirichlet distributions called Pitman-Yor pr...