Etienne Côme
Etienne Côme
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TitreCitée parAnnée
Learning from partially supervised data using mixture models and belief functions
E Côme, L Oukhellou, T Denoeux, P Aknin
Pattern recognition 42 (3), 334-348, 2009
1022009
Model-based count series clustering for bike sharing system usage mining: a case study with the Vélib’system of Paris
C Etienne, O Latifa
ACM Transactions on Intelligent Systems and Technology (TIST) 5 (3), 39, 2014
892014
Model selection and clustering in stochastic block models based on the exact integrated complete data likelihood
E Côme, P Latouche
Statistical Modelling 15 (6), 564-589, 2015
482015
Combined use of sensor data and structural knowledge processed by Bayesian network: Application to a railway diagnosis aid scheme
L Oukhellou, E Come, L Bouillaut, P Aknin
Transportation Research Part C: Emerging Technologies 16 (6), 755-767, 2008
362008
Clustering smart card data for urban mobility analysis
K Mohamed, E Côme, L Oukhellou, M Verleysen
IEEE Transactions on Intelligent Transportation Systems 18 (3), 712-728, 2017
352017
Understanding passenger patterns in public transit through smart card and socioeconomic data
K Mohamed, E Côme, J Baro, L Oukhellou
UrbComp,(Seattle, WA, USA), 2014
342014
The discriminative functional mixture model for a comparative analysis of bike sharing systems
C Bouveyron, E Côme, J Jacques
The Annals of Applied Statistics 9 (4), 1726-1760, 2015
302015
Analyzing year-to-year changes in public transport passenger behaviour using smart card data
AS Briand, E Côme, M Trépanier, L Oukhellou
Transportation Research Part C: Emerging Technologies 79, 274-289, 2017
292017
Spatiotemporal analysis of Bluetooth data: Application to a large urban network
PA Laharotte, R Billot, E Come, L Oukhellou, A Nantes, NE El Faouzi
IEEE Transactions on Intelligent Transportation Systems 16 (3), 1439-1448, 2015
292015
Spatio-temporal analysis of dynamic origin-destination data using latent dirichlet allocation: Application to vélib'bike sharing system of paris
E Come, NA Randriamanamihaga, L Oukhellou, P Aknin
TRB 93rd Annual meeting, 19p, 2014
242014
Clustering the Vélib׳ dynamic Origin/Destination flows using a family of Poisson mixture models
AN Randriamanamihaga, E Côme, L Oukhellou, G Govaert
Neurocomputing 141, 124-138, 2014
222014
Aircraft engine health monitoring using self-organizing maps
E Côme, M Cottrell, M Verleysen, J Lacaille
Industrial Conference on Data Mining, 405-417, 2010
222010
Mixture model estimation with soft labels
E Côme, L Oukhellou, T Denœux, P Aknin
Soft Methods for Handling Variability and Imprecision, 165-174, 2008
192008
Partially supervised independent factor analysis using soft labels elicited from multiple experts: Application to railway track circuit diagnosis
ZL Cherfi, L Oukhellou, E Côme, T Denœux, P Aknin
Soft computing 16 (5), 741-754, 2012
182012
Toward Bicycle Demand Prediction of Large-Scale Bicycle-Sharing System
Y Han, E Côme, L Oukhellou
TRB 93rd Annual meeting, 16p, 2014
162014
Visual mining and statistics for a turbofan engine fleet
J Lacaille, E Côme
Aerospace Conference, 2011 IEEE, 1-8, 2011
162011
Temporal association rule mining for the preventive diagnosis of onboard subsystems within floating train data framework
W Sammouri, E Côme, L Oukhellou, P Aknin, CE Fonlladosa, ...
2012 15th International IEEE Conference on Intelligent Transportation …, 2012
132012
Apprentissage de modèles génératifs pour le diagnostic de systèmes complexes avec labellisation douce et contraintes spatiales
E Côme
Compiègne, 2009
132009
Clustering the Vélib'origin-destinations flows by means of Poisson mixture models.
AN Randriamanamihaga, E Côme, L Oukhellou, G Govaert
ESANN, 2013
122013
Self organizing star (sos) for health monitoring
E Côme, M Cottrell, M Verleysen, J Lacaille
European conference on artificial neural networks,, 99-104, 2010
122010
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