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08/01/2023
Regularization, early-stopping and dreaming: a Hopfield-like setup to address generalization and overfitting
In this work we approach attractor neural networks from a machine learni...
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04/26/2023
Hopfield model with planted patterns: a teacher-student self-supervised learning model
While Hopfield networks are known as paradigmatic models for memory stor...
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11/25/2022
Dense Hebbian neural networks: a replica symmetric picture of supervised learning
We consider dense, associative neural-networks trained by a teacher (i.e...
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11/25/2022
Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning
We consider dense, associative neural-networks trained with no supervisi...
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04/17/2022
Recurrent neural networks that generalize from examples and optimize by dreaming
The gap between the huge volumes of data needed to train artificial neur...
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03/02/2022
Supervised Hebbian learning: toward eXplainable AI
In neural network's Literature, Hebbian learning traditionally refers to...
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09/01/2021
The emergence of a concept in shallow neural networks
We consider restricted Boltzmann machine (RBMs) trained over an unstruct...
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12/02/2019
Interpolating between boolean and extremely high noisy patterns through Minimal Dense Associative Memories
Recently, Hopfield and Krotov introduced the concept of dense associati...
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11/28/2019
Neural networks with redundant representation: detecting the undetectable
We consider a three-layer Sejnowski machine and show that features learn...
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12/21/2018
