activity
20162021
most citedNeural networks with redundant representation: detecting the undetectable

34 citations · 52 across the 5 of their papers we have counts for

collaborators

11 papers

cond-mat.stat-mech20217 cited

PDE/statistical mechanics duality: relation between Guerra's interpolated -spin ferromagnets and the Burgers hierarchy

Alberto Fachechi

We examine the duality relating the equilibrium dynamics of the mean-field -spin ferromagnets at finite size in the Guerra's interpolation scheme and the Burgers hierarchy. In p…

math-ph20213 cited

The relativistic Hopfield model with correlated patterns

Elena Agliari, Alberto Fachechi, Chiara Marullo

In this work we introduce and investigate the properties of the "relativistic" Hopfield model endowed with temporally correlated patterns. First, we review the "relativistic" Hopfi…

cond-mat.dis-nn20196 cited

Interpolating between boolean and extremely high noisy patterns through Minimal Dense Associative Memories

Francesco Alemanno, Martino Centonze, Alberto Fachechi

Recently, Hopfield and Krotov introduced the concept of {\em dense associative memories} [DAM] (close to spin-glasses with -wise interactions in a disordered statistical mechani…

cond-mat.dis-nn201934 cited

Neural networks with redundant representation: detecting the undetectable

Elena Agliari, Francesco Alemanno, Adriano Barra +2

We consider a three-layer Sejnowski machine and show that features learnt via contrastive divergence have a dual representation as patterns in a dense associative memory of order P…

cond-mat.dis-nn2019

Generalized Guerra's interpolation schemes for dense associative neural networks

Elena Agliari, Francesco Alemanno, Adriano Barra +1

In this work we develop analytical techniques to investigate a broad class of associative neural networks set in the high-storage regime. These techniques translate the original st…

cond-mat.dis-nn2018

Dreaming neural networks: rigorous results

Elena Agliari, Francesco Alemanno, Adriano Barra +1

Recently a daily routine for associative neural networks has been proposed: the network Hebbian-learns during the awake state (thus behaving as a standard Hopfield model), then, du…