Etienne Côme
Etienne Côme
Gustave Eiffel University
Verified email at - Homepage
Cited by
Cited by
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, 2016
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), 1-21, 2014
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
The discriminative functional mixture model for a comparative analysis of bike sharing systems
C Bouveyron, E Côme, J Jacques
The Annals of Applied Statistics, 1726-1760, 2015
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
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
Forecasting dynamic public transport origin-destination matrices with long-short term memory recurrent neural networks
F Toqué, E Côme, MK El Mahrsi, L Oukhellou
2016 IEEE 19th international conference on intelligent transportation …, 2016
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
Short & long term forecasting of multimodal transport passenger flows with machine learning methods
F Toqué, M Khouadjia, E Come, M Trepanier, L Oukhellou
2017 IEEE 20th International Conference on Intelligent Transportation …, 2017
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, 2014
A mixture model clustering approach for temporal passenger pattern characterization in public transport
AS Briand, E Côme, MK El Mahrsi, L Oukhellou
International Journal of Data Science and Analytics 1, 37-50, 2016
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
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
Aircraft engine health monitoring using self-organizing maps
E Côme, M Cottrell, M Verleysen, J Lacaille
Advances in Data Mining. Applications and Theoretical Aspects: 10th …, 2010
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 Denoeux, P Aknin
Soft computing 16, 741-754, 2012
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
Mixture model estimation with soft labels
E Côme, L Oukhellou, T Denœux, P Aknin
Soft methods for handling variability and imprecision, 165-174, 2008
Visual mining and statistics for a turbofan engine fleet
J Lacaille, E Côme
2011 Aerospace Conference, 1-8, 2011
Floating train data systems for preventive maintenance: A data mining approach
W Sammouri, E Côme, L Oukhellou, P Aknin, CE Fonlladosa
Proceedings of 2013 International Conference on Industrial Engineering and …, 2013
Toward bicycle demand prediction of large-scale bicycle-sharing system
Y Han, E Côme, L Oukhellou
TRB 93rd Annual meeting, 16p, 2014
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