DE FILIPPO DE GRAZIA, MICHELE

DE FILIPPO DE GRAZIA, MICHELE  

Dipartimento di Psicologia Generale - DPG  

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Titolo Data di pubblicazione Autori Rivista Serie Titolo libro
Parallelization of deep networks 2012 De Grazia, Michele De FilippoStoianov, IvilinZorzi, Marco - - ESANN 2012 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Deep Unsupervised Learning on a Desktop PC: A Primer for Cognitive Scientists 2013 TESTOLIN, ALBERTOSTOIANOV, IVILIN PEEVDE FILIPPO DE GRAZIA, MICHELEZORZI, MARCO FRONTIERS IN PSYCHOLOGY - -
A machine learning approach to QoE-based video admission control and resource allocation in wireless systems 2014 TESTOLIN, ALBERTOZANFORLIN, MARCODE FILIPPO DE GRAZIA, MICHELEMUNARETTO, DANIELEZANELLA, ANDREAZORZI, MARCOZORZI, MICHELE - - Proceedings of the 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET)
A new adaptive videogame for training attention and executive functions: design principles and initial validation 2014 MONTANI, VERONICADE FILIPPO DE GRAZIA, MICHELEZORZI, MARCO FRONTIERS IN PSYCHOLOGY - -
Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence 2015 ZORZI, MICHELEZANELLA, ANDREATESTOLIN, ALBERTODE FILIPPO DE GRAZIA, MICHELEZORZI, MARCO IEEE ACCESS - -
COBANETS: A new paradigm for cognitive communications systems 2016 ZORZI, MICHELEZANELLA, ANDREATESTOLIN, ALBERTODE FILIPPO DE GRAZIA, MICHELEZORZI, MARCO - - 2016 International Conference on Computing, Networking and Communications, ICNC 2016
The role of architectural and learning constraints in neural network models: A case study on visual space coding 2017 Testolin, AlbertoDe Filippo De Grazia, MicheleZorzi, Marco FRONTIERS IN COMPUTATIONAL NEUROSCIENCE - -
On the Relationship between the Underwater Acoustic and Optical Channels 2017 Diamant, RoeeCAMPAGNARO, FILIPPODe Filippo De Grazia, MicheleCasari, PaoloTestolin, AlbertoZorzi, Michele + IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS - -
QoE Multi-Stage Machine Learning for Dynamic Video Streaming 2018 De Grazia, Michele De FilippoZucchetto, DanielTestolin, AlbertoZanella, AndreaZorzi, MarcoZorzi, Michele IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING - -
A Comparison of Shallow and Deep Learning Methods for Predicting Cognitive Performance of Stroke Patients From MRI Lesion Images 2019 Chauhan, SuchetaDe Filippo De Grazia, MicheleCorbetta, MaurizioZorzi, Marco + FRONTIERS IN NEUROINFORMATICS - -
Reply: Lesion network mapping: where do we go from here? 2020 Salvalaggio, AlessandroPini, LorenzoDe Filippo De Grazia, MicheleThiebaut De Schotten, MichelZorzi, MarcoCorbetta, Maurizio BRAIN - -
Post-stroke deficit prediction from lesion and indirect structural and functional disconnection 2020 Salvalaggio A.De Filippo De Grazia M.Zorzi M.Thiebaut de Schotten M.Corbetta M. BRAIN - -
A Systematic Assessment of Feature Extraction Methods for Robust Prediction of Neuropsychological Scores from Functional Connectivity Data 2020 Testolin A.De Filippo De Grazia M.Zorzi M. + - LECTURE NOTES IN ARTIFICIAL INTELLIGENCE Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Assessment of Machine Learning Pipelines for Prediction of Behavioral Deficits from Brain Disconnectomes 2021 Zorzi M.De Filippo De Grazia M.Blini E.Testolin A. - - Lecture Notes in Artificial Intelligence
A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients 2021 Testolin A.De Filippo De Grazia M.Zorzi M. + BRAIN INFORMATICS - -
Reply: Lesion network mapping predicts post-stroke behavioural deficits and improves localization 2021 Salvalaggio ADe Filippo De Grazia MPini LThiebaut De Schotten MZorzi MCorbetta M. BRAIN - -
Prediction of Neuropsychological Scores from Functional Connectivity Matrices Using Deep Autoencoders 2022 Testolin, AlbertoDe Filippo De Grazia, MicheleZorzi, Marco + - LECTURE NOTES IN ARTIFICIAL INTELLIGENCE Lecture Notes in Artificial Intelligence