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Unsupervised and Supervised learning by Dense Associative Memory under replica symmetry breaking
Statistical mechanics of spin glasses is one of the main strands toward a comprehension of information processing by neural networks and learning machines.
Parallel Learning by Multitasking Neural Networks
A modern challenge of Artificial Intelligence is learning multiple patterns at once (i. e. parallel learning).
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.
