48 citations · 170 across the 25 of their papers we have counts for
26 papers
Dense auto-hetero associative memories applied to noisy communication channels
Elena Agliari, Andrea Alessandrelli, Adriano Barra +1
Networks of interacting Hebbian networks have recently been shown to perform a task beyond associative memory, namely \emph{pattern disentanglement}: when fed with a spurious mixtu…
Spectral criteria for generalization in unsupervised Hebbian nets
Elena Agliari, Paulo Duarte Mourão, Alberto Fachechi +1
We consider an unsupervised Hebbian network where the pairwise interactions among neurons are built on noisy realizations of hidden ground-truth vectors. Unlike classical Hopfield…
Multi-channel pattern reconstruction through -directional associative memories
Elena Agliari, Andrea Alessandrelli, Paulo Duarte Mourao +1
We consider -directional associative memories, composed of Hopfield networks, displaying imitative Hebbian intra-network interactions and anti-imitative Hebbian inter-networ…
The importance of being empty: a spectral approach to Hopfield neural networks with diluted examples
Elena Agliari, Alberto Fachechi, Domenico Luongo
We consider Hopfield networks, where neurons interact pair-wise by Hebbian couplings built over . a set of definite patterns (ground truths), . a sample of labeled examples…
The infinite volume limit of the Hopfield neural networks in the replica-symmetric regime
Elena Agliari, Adriano Barra, Pierluigi Bianco +2
Despite extensive research over the past five decades, a rigorous determination of the infinite-volume limit of the free energy of the Hopfield model with an extensive number of pa…
Fundamental operating regimes, hyper-parameter fine-tuning and glassiness: towards an interpretable replica-theory for trained restricted Boltzmann machines
Alberto Fachechi, Elena Agliari, Miriam Aquaro +2
We consider restricted Boltzmann machines with a binary visible layer and a Gaussian hidden layer trained by an unlabelled dataset composed of noisy realizations of a single ground…
A spectral approach to Hebbian-like neural networks
Elena Agliari, Domenico Luongo, Alberto Fachechi
We consider the Hopfield neural network as a model of associative memory and we define its neuronal interaction matrix as a function of a set of binary ve…
Regularization, early-stopping and dreaming: a Hopfield-like setup to address generalization and overfitting
Elena Agliari, Francesco Alemanno, Miriam Aquaro +1
In this work we approach attractor neural networks from a machine learning perspective: we look for optimal network parameters by applying a gradient descent over a regularized los…
Pavlov Learning Machines
Elena Agliari, Miriam Aquaro, Adriano Barra +2
As well known, Hebb's learning traces its origin in Pavlov's Classical Conditioning, however, while the former has been extensively modelled in the past decades (e.g., by Hopfield…
Non-linear PDEs approach to statistical mechanics of Dense Associative Memories
Elena Agliari, Alberto Fachechi, Chiara Marullo
Dense associative memories (DAM), are widespread models in artificial intelligence used for pattern recognition tasks; computationally, they have been proven to be robust against a…
Pattern recognition in Deep Boltzmann machines
Elena Agliari, Linda Albanese, Francesco Alemanno +1
We consider a multi-layer Sherrington-Kirkpatrick spin-glass as a model for deep restricted Boltzmann machines and we solve for its quenched free energy, in the thermodynamic limit…
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…
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…
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…
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…
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…
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…
A novel derivation of the Marchenko-Pastur law through analog bipartite spin-glasses
Elena Agliari, Francesco Alemanno, Adriano Barra +1
In this work we consider the {\em analog bipartite spin-glass} (or {\em real-valued restricted Boltzmann machine} in a neural network jargon), whose variables (those quenched as we…
Dreaming neural networks: forgetting spurious memories and reinforcing pure ones
Alberto Fachechi, Elena Agliari, Adriano Barra
The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maxima…
An evolutionary game model for behavioral gambit of loyalists: Global awareness and risk-aversion
Eleonora Alfinito, Adriano Barra, Matteo Beccaria +2
We study the phase diagram of a minority game where three classes of agents are present. Two types of agents play a risk-loving game that we model by the standard Snowdrift Game. T…
A relativistic extension of Hopfield neural networks via the mechanical analogy
Adriano Barra, Matteo Beccaria, Alberto Fachechi
We propose a modification of the cost function of the Hopfield model whose salient features shine in its Taylor expansion and result in more than pairwise interactions with alterna…
Chiral trace relations in -deformed theories
Matteo Beccaria, Alberto Fachechi, Guido Macorini
We consider gauge theories in four dimensions (pure or mass deformed) and discuss the properties of the simplest chiral observables in the presence of a gene…
Reactive immunization on complex networks
Eleonora Alfinito, Matteo Beccaria, Alberto Fachechi +1
Epidemic spreading on complex networks depends on the topological structure as well as on the dynamical properties of the infection itself. Generally speaking, highly connected ind…
Exact partition functions for deformed theories with flavours
Matteo Beccaria, Alberto Fachechi, Guido Macorini +1
We consider the -deformed gauge theory in four dimensions with massive fundamental hypermultiplets. The low energy effective action depends on…