A modern challenge of Artificial Intelligence is learning multiple patte...
We study bi-directional associative neural networks that, exposed to noi...
We consider dense, associative neural-networks trained by a teacher (i.e...
We consider dense, associative neural-networks trained with no supervisi...
In this paper we investigate the equilibrium properties of bidirectional...
As well known, Hebb's learning traces its origin in Pavlov's Classical
C...
The gap between the huge volumes of data needed to train artificial neur...
In neural network's Literature, Hebbian learning traditionally refers
to...
We consider restricted Boltzmann machine (RBMs) trained over an unstruct...
We consider a three-layer Sejnowski machine and show that features learn...
Recently a daily routine for associative neural networks has been propos...
The standard Hopfield model for associative neural networks accounts for...
We propose a modification of the cost function of the Hopfield model who...
Restricted Boltzmann Machines are described by the Gibbs measure of a
bi...
A specific type of neural network, the Restricted Boltzmann Machine (RBM...