Supervised Hebbian learning: toward eXplainable AI. - Francesco Alemanno; Miriam Aquaro; Ido Kanter; Adriano Barra; Elena Agliari (CoRR, 2022)

From Pavlov Conditioning to Hebb Learning. - Elena Agliari; Miriam Aquaro; Adriano Barra; Alberto Fachechi; Chiara Marullo (Neural Comput., 2023)

Fundamental operating regimes, hyper-parameter fine-tuning and glassiness: towards an interpretable replica-theory for trained restricted Boltzmann machines. - Alberto Fachechi; Elena Agliari; Miriam Aquaro; Anthony Coolen; Menno Mulder (CoRR, 2024)

Hebbian dreaming for small datasets. - Elena Agliari; Francesco Alemanno; Miriam Aquaro; Adriano Barra; Fabrizio Durante; Ido Kanter (Neural Networks, 2024)

Regularization, early-stopping and dreaming: A Hopfield-like setup to address generalization and overfitting. - Elena Agliari; Francesco Alemanno; Miriam Aquaro; Alberto Fachechi (Neural Networks, 2024)

Learning in Associative Networks Through Pavlovian Dynamics. - Daniele Lotito; Miriam Aquaro; Chiara Marullo (Neural Comput., 2025)