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Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning
We consider dense, associative neural-networks trained with no supervision and we investigate their computational capabilities analytically, via a statistical-mechanics approach, and numerically, via Monte Carlo simulations.
Dense Hebbian neural networks: a replica symmetric picture of supervised learning
We consider dense, associative neural-networks trained by a teacher (i. e., with supervision) and we investigate their computational capabilities analytically, via statistical-mechanics of spin glasses, and numerically, via Monte Carlo simulations.
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