M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis et al., A system for largescale machine learning. OSDI Symposium on Operating Systems Design and Implementation, pp.265-283, 2016.

Y. Bengio, A. Courville, and P. Vincent, Representation learning : A review and new perspectives, IEEE transactions on pattern analysis and machine intelligence, vol.35, pp.1798-1828, 2013.

I. Ceapa, C. Smith, and L. Capra, Avoiding the crowds : Understanding tube station congestion patterns from trip data, ACM SIGKDD International Workshop on Urban Computing, pp.134-141, 2012.

T. Chen and C. Guestrin, Xgboost : A scalable tree boosting system. SIGKDD International Conference on Knowledge Discovery and Data mining, pp.785-794, 2016.

K. Cho, B. Van-merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares et al., Learning phrase representations using rnn encoder-decoder for statistical machine translation, EMNLP Empirical Methods in Natural Language Processing, pp.1724-1734, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01433235

F. Chollet, , 2015.

C. Ding, D. Wang, X. Ma, and H. Li, Predicting short-term subway ridership and prioritizing its influential factors using gradient boosting decision trees, Sustainability, vol.8, issue.11, p.1100, 2016.

L. Heydenrijk-ottens, V. Degeler, D. Luo, N. Van-oort, and J. Van-lint, Supervised learning : Predicting passenger load in public transport, 2018.

J. Ke, H. Zheng, H. Yang, and X. M. Chen, Shortterm forecasting of passenger demand under ondemand ride services : A spatio-temporal deep learning approach, Transportation Research Part C : Emerging Technologies, vol.85, pp.591-608, 2017.

N. Lathia and L. Capra, Mining mobility data to minimise travellers' spending on public transport, 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.1181-1189, 2011.

I. Sutskever, J. Martens, G. E. Dahl, and G. E. Hinton, On the importance of initialization and momentum in deep learning, ICML International Conference on Machine Learning, vol.28, p.5, 2013.

F. Toqué, E. Côme, M. K. El-mahrsi, and L. Oukhellou, Forecasting dynamic public transport origin-destination matrices with long-short term memory recurrent neural networks, IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp.1071-1076, 2016.

A. Ziat, E. Delasalles, L. Denoyer, and P. Gallinari, Spatio-temporal neural networks for spacetime series forecasting and relations discovery, IEEE International Conference on Data Mining ICDM, pp.705-714, 2017.
URL : https://hal.archives-ouvertes.fr/hal-02297513