53 citations · 140 across the 8 of their papers we have counts for
9 papers
Earthquake modelling via Brownian motions on networks
Fausto Colantoni, Mirko D'Ovidio, Flavia Tavani
We provide a general model for Brownian motions on metric graphs with interactions. In a general setting, for (sticky) Brownian propagations on edges, our model provides a characte…
Phase transition for the Maki-Thompson rumour model on a small-world network
Elena Agliari, Angelica Pachon, Pablo M. Rodriguez +1
We consider the Maki-Thompson model for the stochastic propagation of a rumour within a population. We extend the original hypothesis of homogenously mixed population by allowing f…
First-passage phenomena in hierarchical networks
Flavia Tavani, Elena Agliari
In this paper we study Markov processes and related first passage problems on a class of weighted, modular graphs which generalize the Dyson hierarchical model. In these networks,…
The exact Laplacian spectrum for the Dyson hierarchical network
Elena Agliari, Flavia Tavani
We consider the Dyson hierarchical graph , that is a weighted fully-connected graph, where the pattern of weights is ruled by the parameter . Exploiting…
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…