21 citations · 23 across the 3 of their papers we have counts for
4 papers
Attention over noisy examples: generalization and memorization in the exponential Hopfield network
Francesco Alemanno
In Hebbian learning from examples, a Hopfield network retrieves archetypes seen only through noisy examples. We study it in the exponential Hopfield model: one softmax attention st…
Dense Hebbian neural networks: a replica symmetric picture of supervised learning
Elena Agliari, Linda Albanese, Francesco Alemanno +5
We consider dense, associative neural-networks trained by a teacher (i.e., with supervision) and we investigate their computational capabilities analytically, via statistical-mecha…
Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning
Elena Agliari, Linda Albanese, Francesco Alemanno +5
We consider dense, associative neural-networks trained with no supervision and we investigate their computational capabilities analytically, via a statistical-mechanics approach, a…
Recurrent neural networks that generalize from examples and optimize by dreaming
Miriam Aquaro, Francesco Alemanno, Ido Kanter +3
The gap between the huge volumes of data needed to train artificial neural networks and the relatively small amount of data needed by their biological counterparts is a central puz…