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Francesco Alemanno
Francesco Alemanno
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Cited by
Cited by
Year
Neural networks with a redundant representation: Detecting the undetectable
E Agliari, F Alemanno, A Barra, M Centonze, A Fachechi
Physical review letters 124 (2), 028301, 2020
322020
Generalized Guerra’s interpolation schemes for dense associative neural networks
E Agliari, F Alemanno, A Barra, A Fachechi
Neural Networks 128, 254-267, 2020
302020
The emergence of a concept in shallow neural networks
E Agliari, F Alemanno, A Barra, G De Marzo
Neural Networks 148, 232-253, 2022
272022
Supervised hebbian learning
F Alemanno, M Aquaro, I Kanter, A Barra, E Agliari
Europhysics Letters 141 (1), 11001, 2023
24*2023
Dreaming neural networks: rigorous results
E Agliari, F Alemanno, A Barra, A Fachechi
Journal of Statistical Mechanics: Theory and Experiment 2019 (8), 083503, 2019
212019
Replica symmetry breaking in dense hebbian neural networks
L Albanese, F Alemanno, A Alessandrelli, A Barra
Journal of Statistical Physics 189 (2), 24, 2022
152022
A transport equation approach for deep neural networks with quenched random weights
E Agliari, L Albanese, F Alemanno, A Fachechi
Journal of Physics A: Mathematical and Theoretical 54 (50), 505004, 2021
11*2021
Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning
E Agliari, L Albanese, F Alemanno, A Alessandrelli, A Barra, F Giannotti, ...
arXiv preprint arXiv:2211.14067, 2022
102022
Outperforming RBM feature-extraction capabilities by “dreaming” mechanism
A Fachechi, A Barra, E Agliari, F Alemanno
IEEE transactions on neural networks and learning systems, 2022
102022
Fully automated computational approach for precisely measuring organelle acidification with optical ph sensors
A Chandra, S Prasad, F Alemanno, M De Luca, R Rizzo, R Romano, ...
ACS Applied Materials & Interfaces 14 (16), 18133-18149, 2022
82022
Interpolating between Boolean and extremely high noisy patterns through minimal dense associative memories
F Alemanno, M Centonze, A Fachechi
Journal of Physics A: Mathematical and Theoretical 53 (7), 074001, 2020
42020
On the Marchenko–Pastur law in analog bipartite spin-glasses
E Agliari, F Alemanno, A Barra, A Fachechi
Journal of Physics A: Mathematical and Theoretical 52 (25), 254002, 2019
42019
Hopfield model with planted patterns: A teacher-student self-supervised learning model
F Alemanno, L Camanzi, G Manzan, D Tantari
Applied Mathematics and Computation 458, 128253, 2023
32023
Regularization, early-stopping and dreaming: a Hopfield-like setup to address generalization and overfitting
E Agliari, M Aquaro, F Alemanno, A Fachechi
arXiv preprint arXiv:2308.01421, 2023
32023
Probing single-cell fermentation fluxes and exchange networks via pH-sensing hybrid nanofibers
V Onesto, S Forciniti, F Alemanno, K Narayanankutty, A Chandra, ...
ACS nano 17 (4), 3313-3323, 2022
32022
Recurrent neural networks that generalize from examples and optimize by dreaming
M Aquaro, F Alemanno, I Kanter, F Durante, E Agliari, A Barra
arXiv preprint arXiv:2204.07954, 2022
32022
Hebbian dreaming for small datasets
E Agliari, F Alemanno, M Aquaro, A Barra, F Durante, I Kanter
Neural Networks, 106174, 2024
22024
Dense Hebbian neural networks: A replica symmetric picture of unsupervised learning
E Agliari, L Albanese, F Alemanno, A Alessandrelli, A Barra, F Giannotti, ...
Physica A: Statistical Mechanics and its Applications 627, 129143, 2023
22023
Quantifying heterogeneity to drug response in cancer–stroma kinetics
F Alemanno, M Cavo, D Delle Cave, A Fachechi, R Rizzo, E D’Amone, ...
Proceedings of the National Academy of Sciences 120 (11), e2122352120, 2023
22023
Analysis of temporal correlation in heart rate variability through maximum entropy principle in a minimal pairwise glassy model
E Agliari, F Alemanno, A Barra, OA Barra, A Fachechi, LF Vento, L Moretti
Scientific Reports 10 (1), 15353, 2020
22020
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