We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
We study the problem of learning regular tree languages from text. We show that the framework of function distinguishability as introduced by the author in Theoretical Computer Sc...
We address the topic of specifying multi-agent systems using the situation and state calculus (SSC). SSC has been proposed as an extension of the situation calculus to overcome so...
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are d...
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...