Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...
We consider the Contextual Recursive Cascade Correlation model (CRCC), a model able to learn contextual mappings in structured domains. We propose a formal characterization of the ...
This paper explores basic aspects of the immune system and proposes a novel immune network model with the main goals of clustering and filtering unlabeled numerical data sets. It ...
A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically r...
The hippocampus is known to be involved in spatial learning in rats. Spatial learning involves the encoding and replay of temporally sequenced spatial information. Temporally seque...