Post-stroke deficit prediction from lesion and indirect structural and functional disconnection A Salvalaggio, M De Filippo De Grazia, M Zorzi, M Thiebaut de Schotten, ... Brain 143 (7), 2173-2188, 2020 | 192 | 2020 |
Cognition-Based Networks: a New Perspective on Network Optimization Using Learning and Distributed Intelligence M Zorzi, A Zanella, A Testolin, M De Filippo De Grazia, M Zorzi IEEE, 2015 | 156 | 2015 |
A comparison of shallow and deep learning methods for predicting cognitive performance of stroke patients from MRI lesion images S Chauhan, L Vig, M De Filippo De Grazia, M Corbetta, S Ahmad, M Zorzi Frontiers in neuroinformatics 13, 53, 2019 | 80 | 2019 |
A machine learning approach to QoE-based video admission control and resource allocation in wireless systems A Testolin, M Zanforlin, MDF De Grazia, D Munaretto, A Zanella, M Zorzi, ... 2014 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET), 31-38, 2014 | 64 | 2014 |
A new adaptive videogame for training attention and executive functions: design principles and initial validation V Montani, M De Filippo De Grazia, M Zorzi Frontiers in Psychology 5, 409, 2014 | 60 | 2014 |
Deep unsupervised learning on a desktop PC: A primer for cognitive scientists A Testolin, I Stoianov, M De Filippo De Grazia, M Zorzi Frontiers in Psychology 4, 251, 2013 | 44 | 2013 |
On the relationship between the underwater acoustic and optical channels R Diamant, F Campagnaro, MDF De Grazia, P Casari, A Testolin, ... IEEE Transactions on Wireless Communications 16 (12), 8037-8051, 2017 | 42 | 2017 |
Recovery of neural dynamics criticality in personalized whole-brain models of stroke RP Rocha, L Koçillari, S Suweis, M De Filippo De Grazia, MT de Schotten, ... Nature Communications 13 (1), 3683, 2022 | 33 | 2022 |
QoE multi-stage machine learning for dynamic video streaming MDF De Grazia, D Zucchetto, A Testolin, A Zanella, M Zorzi, M Zorzi IEEE Transactions on Cognitive Communications and Networking 4 (1), 146-161, 2017 | 26 | 2017 |
A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients F Calesella, A Testolin, M De Filippo De Grazia, M Zorzi Brain Informatics 8 (1), 8, 2021 | 21 | 2021 |
A novel stroke lesion network mapping approach: improved accuracy yet still low deficit prediction L Pini, A Salvalaggio, M De Filippo De Grazia, M Zorzi, ... Brain communications 3 (4), fcab259, 2021 | 20 | 2021 |
The role of architectural and learning constraints in neural network models: a case study on visual space coding A Testolin, M De Filippo De Grazia, M Zorzi Frontiers in computational neuroscience 11, 13, 2017 | 19 | 2017 |
Application of the preference learning model to a human resources selection task F Aiolli, M De Filippo De Grazia, A Sperduti Computational Intelligence and Data Mining, 2009. CIDM'09. IEEE Symposium on …, 2009 | 19 | 2009 |
Parallelization of Deep Networks M De Filippo De Grazia, I Stoianov, M Zorzi European Symposium on Artificial Neural Networks, Computational Intelligence …, 2012 | 18* | 2012 |
Sensorimotor, attentional, and neuroanatomical predictors of upper limb motor deficits and rehabilitation outcome after stroke D D’Imperio, Z Romeo, L Maistrello, E Durgoni, C Della Pietà, ... Neural plasticity 2021 (1), 8845685, 2021 | 16 | 2021 |
Reply: Lesion network mapping predicts post-stroke behavioural deficits and improves localization A Salvalaggio, M De Filippo De Grazia, L Pini, M Thiebaut De Schotten, ... Brain 144 (4), e36-e36, 2021 | 14 | 2021 |
Reply: Lesion network mapping: where do we go from here? A Salvalaggio, L Pini, M De Filippo De Grazia, M Thiebaut De Schotten, ... Brain 144 (1), e6-e6, 2021 | 14 | 2021 |
A developmental approach for training deep belief networks M Zambra, A Testolin, M Zorzi Cognitive Computation 15 (1), 103-120, 2023 | 8 | 2023 |
Space coding for sensorimotor transformations can emerge through unsupervised learning M De Filippo De Grazia, S Cutini, M Lisi, M Zorzi Cognitive processing 13 (1), 141-146, 2012 | 7 | 2012 |
A systematic assessment of feature extraction methods for robust prediction of neuropsychological scores from functional connectivity data F Calesella, A Testolin, M De Filippo De Grazia, M Zorzi International conference on brain informatics, 29-40, 2020 | 5 | 2020 |