collaborators

6 papers

cond-mat.dis-nn2026

Serial vs parallel recall in the Blume-Every-Griffiths neural networks

Linda Albanese, Andrea Alessandrelli, Adriano Barra +1

Fully connected Blume-Emery-Griffiths neural networks performing pattern recognition and associative memory have been heuristically studied in the past (mainly via the replica tric…

cond-mat.dis-nn2025

Yet another exponential Hopfield model

Linda Albanese, Andrea Alessandrelli, Adriano Barra +1

We propose and analyze a new variation of the so-called {\em exponential Hopfield model}, a recently introduced family of associative neural networks with unprecedented storage cap…

cond-mat.dis-nn2025

Supervised and Unsupervised protocols for hetero-associative neural networks

Andrea Alessandrelli, Adriano Barra, Andrea Ladiana +2

This paper introduces a learning framework for Three-Directional Associative Memory (TAM) models, extending the classical Hebbian paradigm to both supervised and unsupervised proto…

cond-mat.dis-nn2025

Guerra interpolation for inverse freezing

Linda Albanese, Adriano Barra, Emilio N. M. Cirillo

In these short notes, we adapt and systematically apply Guerra's interpolation techniques on a class of disordered mean-field spin glasses equipped with crystal fields and multi-va…

cond-mat.dis-nn2025

Beyond Disorder: Unveiling Cooperativeness in Multidirectional Associative Memories

Andrea Alessandrelli, Adriano Barra, Andrea Ladiana +2

By leveraging tools from the statistical mechanics of complex systems, in these short notes we extend the architecture of a neural network for hetero-associative memory (called thr…

cond-mat.dis-nn2025

Networks of neural networks: more is different

Elena Agliari, Andrea Alessandrelli, Adriano Barra +2

The common thread behind the recent Nobel Prize in Physics to John Hopfield and those conferred to Giorgio Parisi in 2021 and Philip Anderson in 1977 is disorder. Quoting Philip An…