Pietro Barbiero, P Barbiero, Pietro B
Pietro Barbiero, P Barbiero, Pietro B
University of Cambridge
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Citata da
Citata da
An Individual’s Connection to Nature Can Affect Perceived Restorativeness of Natural Environments. Some Observations about Biophilia
R Berto, G Barbiero, P Barbiero, G Senes
Behavioral Sciences 8 (3), 34, 2018
The GH-EXIN neural network for hierarchical clustering
G Cirrincione, G Ciravegna, P Barbiero, V Randazzo, E Pasero
Neural Networks 121, 57-73, 2020
Supervised Gene Identification in Colorectal Cancer
P Barbiero, A Bertotti, G Ciravegna, G Cirrincione, E Pasero, E Piccolo
Italian Workshop on Neural Networks (WIRN 2017), 2017
Forecasting ultra-early intensive care strain from COVID-19 in England
J Deasy, E Rocheteau, K Kohler, DJ Stubbs, P Barbiero, P Li˛, A Ercole
medRxiv, 2020
Neural Biclustering in Gene Expression Analysis
P Barbiero, A Bertotti, G Ciravegna, G Cirrincione, E Pasero, E Piccolo
CSCI'17 (The 2017 International Conference on Computational Science andá…, 2017
Assessing discriminating capability of geometrical descriptors for 3D face recognition by using the GH-EXIN neural network
G Ciravegna, G Cirrincione, F Marcolin, P Barbiero, N Dagnes, E Piccolo
Neural Approaches to Dynamics of Signal Exchanges, 223-233, 2020
Uncovering Coresets for Classification With Multi-Objective Evolutionary Algorithms
P Barbiero, G Squillero, A Tonda
arXiv preprint arXiv:2002.08645, 2020
DNA Microarray Classification: Evolutionary Optimization of Neural Network Hyper-parameters
P Barbiero, A Bertotti, G Ciravegna, G Cirrincione, E Piccolo
Neural Approaches to Dynamics of Signal Exchanges, 305-311, 2020
Modeling Generalization in Machine Learning: A Methodological and Computational Study
P Barbiero, G Squillero, A Tonda
arXiv preprint arXiv:2006.15680, 2020
The Computational Patient has Diabetes and a COVID
P Barbiero, P Liˇ
arXiv preprint arXiv:2006.06435, 2020
Shallow versus Deep Neural Networks in Gear Fault Diagnosis
G Cirrincione, RR Kumar, A Mohammadi, SH Kia, P Barbiero, J Ferretti
IEEE Transactions on Energy Conversion, 2020
Towards Uncovering Feature Extraction From Temporal Signals in Deep CNN: the ECG Case Study
J Ferretti, P Barbiero, V Randazzo, G Cirrincione, E Pasero
2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020
Unsupervised Multi-omic Data Fusion: The Neural Graph Learning Network
P Barbiero, M Lovino, M Siviero, G Ciravegna, V Randazzo, E Ficarra, ...
International Conference on Intelligent Computing, 172-182, 2020
Graph representation forecasting of patient's medical conditions: towards a digital twin
P Barbiero, RV TornÚ, P Liˇ
arXiv preprint arXiv:2009.08299, 2020
Gradient-based Competitive Learning: Theory
G Cirrincione, P Barbiero, G Ciravegna, V Randazzo
arXiv preprint arXiv:2009.02799, 2020
Understanding Abstraction in Deep CNN: An Application on Facial Emotion Recognition
F Nonis, P Barbiero, G Cirrincione, EC Olivetti, F Marcolin, E Vezzetti
Progresses in Artificial Intelligence and Neural Systems, 281-290, 2020
A Novel Outlook on Feature Selection as a Multi-objective Problem
P Barbiero, E Lutton, G Squillero, A Tonda
International Conference on Artificial Evolution (Evolution Artificielle), 68-81, 2019
Neural Epistemology in Dynamical System Learning
P Barbiero, C Giansalvo, C Maurizio, P Elio, V Francesco
Italia Workshop on Neural Networks, 2018
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