We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
To increase the relevancy of local patterns discovered from noisy relations, it makes sense to formalize error-tolerance. Our starting point is to address the limitations of state...
— This paper presents an original method to tune a neuromimetic IC based on neuron conductance-based models (Hodgkin-Huxley formalism). This method is well known in electrophysio...
In order to facilitate incremental modeling and analysis of fault-tolerant embedded systems, we introduce an object analysis pattern, called the detector pattern, that provides a ...
The paper deals with on-board planning for a satellite swarm via communication and negotiation. We aim at defining individual behaviours that result in a global behaviour that me...