6 papers
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…
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…
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…
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…
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…
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…