A statistical mechanics approach to Granovetter theory - Adriano Barra; Elena Agliari (CoRR, 2010)

Continuous-Time Quantum Walks and Trapping. - Elena Agliari; Oliver Mülken; Alexander Blumen (Int. J. Bifurc. Chaos, 2010)

Percolation on correlated random networks - Elena Agliari; Claudia Cioli; Enore Guadagnini (CoRR, 2011)

Parallel retrieval of correlated patterns: From Hopfield networks to Boltzmann machines. - Elena Agliari; Adriano Barra; Andrea De Antoni; Andrea Galluzzi (Neural Networks, 2013)

A Walk in the Statistical Mechanical Formulation of Neural Networks - Alternative Routes to Hebb Prescription. - Elena Agliari; Adriano Barra; Andrea Galluzzi; Daniele Tantari; Flavia Tavani (IJCCI (NCTA), 2014)

Multitasking attractor networks with neuronal threshold noise. - Elena Agliari; Adriano Barra; Andrea Galluzzi; Marco Isopi (Neural Networks, 2014)

Instability and network effects in innovative markets. - Paolo Sgrignoli; Elena Agliari; Raffaella Burioni; Augusto Schianchi (Math. Comput. Simul., 2015)

Hierarchical neural networks perform both serial and parallel processing. - Elena Agliari; Adriano Barra; Andrea Galluzzi; Francesco Guerra 002; Daniele Tantari; Flavia Tavani (Neural Networks, 2015)

Complex Reaction Kinetics in Chemistry: A Unified Picture Suggested by Mechanics in Physics. - Elena Agliari; Adriano Barra; Giulio Landolfi; Sara Murciano; Sarah Perrone (Complex., 2018)

Dreaming neural networks: rigorous results. - Elena Agliari; Francesco Alemanno; Adriano Barra; Alberto Fachechi (CoRR, 2018)

Dreaming neural networks: Forgetting spurious memories and reinforcing pure ones. - Alberto Fachechi; Elena Agliari; Adriano Barra (Neural Networks, 2019)

Generalized Guerra's interpolation schemes for dense associative neural networks. - Elena Agliari; Francesco Alemanno; Adriano Barra; Alberto Fachechi (Neural Networks, 2020)

Boltzmann Machines as Generalized Hopfield Networks: A Review of Recent Results and Outlooks. - Chiara Marullo; Elena Agliari (Entropy, 2021)

On the effective initialisation for restricted Boltzmann machines via duality with Hopfield model. - Francesca Elisa Leonelli; Elena Agliari; Linda Albanese; Adriano Barra (Neural Networks, 2021)

Storing, learning and retrieving biased patterns. - Elena Agliari; Francesca Elisa Leonelli; Chiara Marullo (Appl. Math. Comput., 2022)

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

The emergence of a concept in shallow neural networks. - Elena Agliari; Francesco Alemanno; Adriano Barra; Giordano De Marzo (Neural Networks, 2022)

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

A spectral approach to Hebbian-like neural networks. - Elena Agliari; Alberto Fachechi; Domenico Luongo (Appl. Math. Comput., 2024)

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)

Outperforming RBM Feature-Extraction Capabilities by "Dreaming" Mechanism. - Alberto Fachechi; Adriano Barra; Elena Agliari; Francesco Alemanno (IEEE Trans. Neural Networks Learn. Syst., 2024)