6 papers
Exponential Capacity in Multilayer Hetero-Associative Neural Networks
Elena Agliari, Adriano Barra, Andrea Ladiana +1
Exponential Hopfield networks store a number of patterns that grows exponentially with the number of neurons, and in their classical formulation they are auto-associative: they com…
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…
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…
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…
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…
Generalized hetero-associative neural networks
Elena Agliari, Andrea Alessandrelli, Adriano Barra +2
Auto-associative neural networks (e.g., the Hopfield model implementing the standard Hebbian prescription) serve as a foundational framework for pattern recognition and associative…