Lorenzo Livi
Lorenzo Livi
University of Manitoba and University of Exeter
Verified email at - Homepage
Cited by
Cited by
Graph neural networks with convolutional arma filters
FM Bianchi, D Grattarola, L Livi, C Alippi
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
The graph matching problem
L Livi, A Rizzi
Pattern Analysis and Applications 16 (3), 253-283, 2013
Granular computing, computational intelligence, and the analysis of non-geometric input spaces
L Livi, A Sadeghian
Granular Computing 1 (1), 13-20, 2016
Investigating echo-state networks dynamics by means of recurrence analysis
FM Bianchi, L Livi, C Alippi
IEEE transactions on neural networks and learning systems 29 (2), 427-439, 2016
Use of nivolumab in elderly patients with advanced squamous non–small-cell lung cancer: results from the Italian cohort of an expanded access programme
F Grossi, L Crin˛, A Logroscino, S Canova, A Delmonte, B Melotti, C Proto, ...
European Journal of Cancer 100, 126-134, 2018
Determination of the edge of criticality in echo state networks through Fisher information maximization
L Livi, FM Bianchi, C Alippi
IEEE transactions on neural networks and learning systems 29 (3), 706-717, 2017
Efficacy of nivolumab in pre-treated non-small-cell lung cancer patients harbouring KRAS mutations
F Passiglia, F Cappuzzo, O Alabiso, AC Bettini, P Bidoli, R Chiari, ...
British journal of cancer 120 (1), 57-62, 2019
Modeling and recognition of smart grid faults by a combined approach of dissimilarity learning and one-class classification
E De Santis, L Livi, A Sadeghian, A Rizzi
Neurocomputing 170, 368-383, 2015
A granular computing approach to the design of optimized graph classification systems
FM Bianchi, L Livi, A Rizzi, A Sadeghian
Soft Computing 18 (2), 393-412, 2014
Learning representations of multivariate time series with missing data
FM Bianchi, L Livi, Kě Mikalsen, M Kampffmeyer, R Jenssen
Pattern Recognition 96, 106973, 2019
Concept Drift and Anomaly Detection in Graph Streams
D Zambon, C Alippi, L Livi
IEEE Transactions on Neural Networks and Learning Systems, 1-14, 2018
Optimized dissimilarity space embedding for labeled graphs
L Livi, A Rizzi, A Sadeghian
Information Sciences 266, 47-64, 2014
Interpreting recurrent neural networks behaviour via excitable network attractors
A Ceni, P Ashwin, L Livi
Cognitive Computation 12 (2), 330-356, 2020
Deep divergence-based approach to clustering
M Kampffmeyer, S L°kse, FM Bianchi, L Livi, AB Salberg, R Jenssen
Neural Networks 113, 91-101, 2019
On the impact of topological properties of smart grids in power losses optimization problems
F Possemato, M Paschero, L Livi, A Rizzi, A Sadeghian
International Journal of Electrical Power & Energy Systems 78, 755-764, 2016
Interval type-2 fuzzy sets to model linguistic label perception in online services satisfaction
M Moharrer, H Tahayori, L Livi, A Sadeghian, A Rizzi
Soft Computing 19 (1), 237-250, 2015
On the problem of modeling structured data with the MinSOD representative
G Del Vescovo, L Livi, FMF Mascioli, A Rizzi
International Journal of Computer Theory and Engineering 6 (1), 9, 2014
Multiplex visibility graphs to investigate recurrent neural network dynamics
FM Bianchi, L Livi, C Alippi, R Jenssen
Scientific reports 7 (1), 1-13, 2017
Two density-based k-means initialization algorithms for non-metric data clustering
FM Bianchi, L Livi, A Rizzi
Pattern Analysis and Applications 19 (3), 745-763, 2016
Graph ambiguity
L Livi, A Rizzi
Fuzzy Sets and Systems 221, 24-47, 2013
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