We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
This paper describes an evaluation of a neural network technique for modelling fuel spray penetration in the cylinder of a diesel internal combustion engine. The model was implemen...
Simon D. Walters, Shaun H. Lee, Cyril Crua, Robert...
Many neural networks, such as the complex cortical networks of the mammalian brain, are organized in multiple clusters, with many connections within but few links between clusters...
In this paper we show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. The hyperbolic geometry can be used to facilitate maximally ef...
Fragkiskos Papadopoulos, Dmitri V. Krioukov, Mari&...
A binary constraints network consists of a set of n variables, defined on domains of size at most d, and a set of e binary constraints. The binary constraint satisfaction problem ...