129 citations · 318 across the 16 of their papers we have counts for
10 papers · 1 filter
Beyond catastrophic forgetting in associative networks with self-interactions
Gianni V. Vinci, Andrea Galluzzi, Maurizio Mattia
Spin-glass models of associative memories are a cornerstone between statistical physics and theoretical neuroscience. In these networks, stochastic spin-like units interact through…
Topological properties of hierarchical networks
Elena Agliari, Adriano Barra, Andrea Galluzzi +3
Hierarchical networks are attracting a renewal interest for modelling the organization of a number of biological systems and for tackling the complexity of statistical mechanical m…
Hierarchical neural networks perform both serial and parallel processing
Elena Agliari, Adriano Barra, Andrea Galluzzi +3
In this work we study a Hebbian neural network, where neurons are arranged according to a hierarchical architecture such that their couplings scale with their reciprocal distance.…
A walk in the statistical mechanical formulation of neural networks
Elena Agliari, Adriano Barra, Andrea Galluzzi +2
Neural networks are nowadays both powerful operational tools (e.g., for pattern recognition, data mining, error correction codes) and complex theoretical models on the focus of sci…
Meta-stable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network
Elena Agliari, Adriano Barra, Andrea Galluzzi +3
In this paper we introduce and investigate the statistical mechanics of hierarchical neural networks: First, we approach these systems à la Mattis, by thinking at the Dyson model a…
From Dyson to Hopfield: Processing on hierarchical networks
Elena Agliari, Adriano Barra, Andrea Galluzzi +3
We consider statistical-mechanical models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling d…
Mean field bipartite spin models treated with mechanical techniques
Adriano Barra, Andrea Galluzzi, Francesco Guerra +2
Inspired by a continuously increasing interest in modeling and framing complex systems in a thermody- namic rationale, in this paper we continue our investigation in adapting well…
Multitasking network with fast noise
Elena Agliari, Adriano Barra, Andrea Galluzzi +1
We consider the multitasking associative network in the low-storage limit and we study its phase diagram with respect to the noise level and the degree of dilution in patte…
Parallel retrieval of correlated patterns
Elena Agliari, Adriano Barra, Andrea De Antoni +1
In this work, we first revise some extensions of the standard Hopfield model in the low storage limit, namely the correlated attractor case and the multitasking case recently intro…
Multitasking associative networks
Elena Agliari, Adriano Barra, Andrea Galluzzi +2
We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able…