Nicolò Navarin
Title
Cited by
Cited by
Year
Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’
E Lavezzo, E Franchin, C Ciavarella, G Cuomo-Dannenburg, L Barzon, ...
Nature 584 (7821), 425-429, 2020
963*2020
LSTM networks for data-aware remaining time prediction of business process instances
N Navarin, B Vincenzi, M Polato, A Sperduti
2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017
562017
A tree-based kernel for graphs.
G Da San Martino, N Navarin, A Sperduti
Twelfth SIAM International Conference on Data Mining, 975-986, 2012
452012
On Filter Size in Graph Convolutional Networks
D Van Tran, N Navarin, A Sperduti
2018 IEEE Symposium Series on Computational Intelligence (SSCI), 1534-1541, 2018
352018
Multi-task learning for the prediction of wind power ramp events with deep neural networks
M Dorado-Moreno, N Navarin, PA Gutiérrez, L Prieto, A Sperduti, ...
Neural Networks 123, 401-411, 2020
222020
Multiple Graph-Kernel Learning
F Aiolli, M Donini, N Navarin, A Sperduti
IEEE Symposium on Computational Intelligence and Data Mining, 2015
212015
Tree-based kernel for graphs with continuous attributes
G Da San Martino, N Navarin, A Sperduti
IEEE transactions on neural networks and learning systems 29 (7), 3270-3276, 2017
202017
Ordered Decompositional DAG Kernels Enhancements
G Da San Martino, N Navarin, A Sperduti
Neurocomputing 192, 92-103, 2016
192016
A lossy counting based approach for learning on streams of graphs on a budget
G Da San Martino, N Navarin, A Sperduti
Proceedings of the Twenty-Third international joint conference on Artificial …, 2013
192013
Scuba: scalable kernel-based gene prioritization
G Zampieri, D Van Tran, M Donini, N Navarin, F Aiolli, A Sperduti, G Valle
BMC bioinformatics 19 (1), 1-12, 2018
182018
A memory efficient graph kernel
G Da San Martino, N Navarin, A Sperduti
Neural Networks (IJCNN), The 2012 International Joint Conference on, 1-7, 2012
172012
Pre-training graph neural networks with kernels
N Navarin, DV Tran, A Sperduti
arXiv preprint arXiv:1811.06930, 2018
152018
Explainable predictive process monitoring
R Galanti, B Coma-Puig, M de Leoni, J Carmona, N Navarin
2020 2nd International Conference on Process Mining (ICPM), 1-8, 2020
142020
Measuring the expressivity of graph kernels through statistical learning theory
L Oneto, N Navarin, M Donini, A Sperduti, F Aiolli, D Anguita
Neurocomputing 268, 4-16, 2017
142017
Universal readout for graph convolutional neural networks
N Navarin, D Van Tran, A Sperduti
2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019
112019
Imperial College London COVID-19 Response Team, Alessandra R Brazzale, Stefano Toppo, Marta Trevisan, Vincenzo Baldo, Christl A
E Lavezzo, E Franchin, C Ciavarella, G Cuomo-Dannenburg, L Barzon, ...
medRxiv, 2020
92020
An efficient graph kernel method for non-coding RNA functional prediction
N Navarin, F Costa
Bioinformatics 33 (17), 2642-2650, 2017
92017
Approximated Neighbours MinHash Graph Node Kernel
N Navarin, A Sperduti
ESANN 2017 proceedings, European Symposium on Artificial Neural Networks …, 2017
82017
Hyper-parameter tuning for graph kernels via multiple kernel learning
CM Massimo, N Navarin, A Sperduti
International Conference on Neural Information Processing, 214-223, 2016
82016
Exploiting the ODD framework to define a novel effective graph kernel
G Da San Martino, N Navarin, A Sperduti
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2015
82015
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Articles 1–20