Unpublished working papers


  • Xiaochun Meng, James W. Taylor, Souhaib Ben Taieb, Siran Li (2021) Scoring Functions for Multivariate Distributions and Level Sets. Abstract  pdf

Published articles


  • Souhaib Ben Taieb (2022) Learning Quantile Functions for Temporal Point Processes with Recurrent Neural Splines. Proceedings of the 25 th International Conference on Artificial Intelligence and Statistics (AISTATS) 2022, Valencia, Spain. PMLR, Volume 151.. Abstract  pdf
  • Fotios Petropoulos, et al. (2022) Forecasting: theory and practice. International Journal of Forecasting.. Abstract Arxiv
  • Souhaib Ben Taieb and Kathryn S. Taylor (2022) Commentary on “Transparent modelling of influenza incidence”: On big data models for infectious disease forecasting. Abstract Online


  • Cameron Roach, Rob J Hyndman, Souhaib Ben Taieb (2021) Nonlinear mixed effects models for time series forecasting of smart meter demand. Journal of Forecasting 40(6), 1118-1130. Abstract  pdf
  • Chiara Di , Modica Pierre Pinson, Souhaib Ben Taieb (2021) Online forecast reconciliation in wind power prediction. Electric Power Systems Research, Volume 190, 2021. Abstract DOI


  • Souhaib Ben Taieb, James W Taylor, Rob J Hyndman (2020) Hierarchical Probabilistic Forecasting of Electricity Demand with Smart Meter Data. J. American Statistical Association, 6(0), 1-17. Abstract DOI  pdf


  • D Vicendese, L Te Marvelde, PD McNair, K Whitfield, DR English, S Ben Taieb, RJ Hyndman, R Thomas (2019) Hospital characteristics, rather than surgical volume, predict length of stay following colorectal cancer surgery. Australian and New Zealand Journal of Public Health, 44: 73-82. Abstract DOI
  • Souhaib Ben Taieb and Bonsoo Koo (2019) Regularized regression for hierarchical forecasting without unbiasdness conditions. Proceedings of Knowledge Discovery and Data Mining (KDD), 2019.. Abstract Online  pdf


  • Souhaib Ben Taieb, James W Taylor, Rob J Hyndman (2017) Coherent Probabilistic Forecasts for Hierarchical Time Series. Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3348-3357. Abstract Online  pdf
  • Souhaib Ben Taieb, Jiafan Yu, Mateus Neves Barreto and Ram Rajagopal (2017) Regularization in Hierarchical Time Series Forecasting With Application to Electricity Smart Meter Data. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. AAAI Press, 2017.. Abstract Online  pdf
  • Souhaib Ben Taieb (2017) Sparse and Smooth Adjustments for Coherent Forecasts in Temporal Aggregation of Time Series. NIPS 2016 Time Series Workshop, JMLR W&CP Vol. 55, 2017.. Abstract Online  pdf


  • Souhaib Ben Taieb, Raphael Huser, Rob J Hyndman and Marc G Genton (2016) Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression. IEEE Transactions on Smart Grid 7(5), 2448-2455. Abstract DOI  pdf
  • Souhaib Ben Taieb and Amir F. Atiya (2016) A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting. IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 1, pp. 62-76, 2016. Abstract Online  pdf


  • Souhaib Ben Taieb (2014) Machine learning strategies for multi-step-ahead time series forecasting. PhD thesis, Free University of Brussels. Abstract  pdf
  • Souhaib Ben Taieb, Rob J Hyndman (2014) A gradient boosting approach to the Kaggle load forecasting competition. International Journal of Forecasting 30(2), 382–394. Abstract DOI  pdf
  • Souhaib Ben Taieb, Rob J Hyndman (2014) Boosting multi-step autoregressive forecasts. Proceedings of the International Conference on Machine Learning (ICML), Beijing, China. Abstract  pdf


  • Liran Lerman, Gianluca Bontempi, Souhaib Ben Taieb and Olivier Markowitch (2013) A Time Series Approach for Profiling Attack. Lecture Notes in Computer Science, Volume 8204, 75-94, 2013. Abstract Online
  • Gianluca Bontempi, Souhaib Ben Taieb and Y.-A. Le Borgne (2013) Machine Learning Strategies for Time Series Forecasting. Business Intelligence, Vol. 138. Springer, pp.62–77, 2013.. Abstract Online


  • Souhaib Ben Taieb, Gianluca Bontempi, Amir F. Atiya and Antti Sorjamaa (2012) A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition. Expert Systems with Applications, 39(8):7067–7083, 2012.. Abstract Online
  • Alfredo Vaccaro, Gianluca Bontempi, Souhaib Ben Taieb and Domenico Villacci (2012) Adaptive local learning techniques for multiple-step-ahead wind speed forecasting. Electric Power Systems Research, 83(1):129–135, 2012.. Abstract Online


  • Souhaib Ben Taieb and Gianluca Bontempi (2011) Recursive Multi-step Time Series Forecasting by Perturbing Data. IEEE International Conference on Data Mining (ICDM), December, 2011.. Abstract Online
  • Alfredo Vaccaro, Gianluca Bontempi, Souhaib Ben Taieb and Domenico Villacci (2011) Conditionally dependent strategies for multiple-step-ahead prediction in local learning. International Journal of Forecasting, 27(3):689–699, 2011.. Abstract Online


  • Souhaib Ben Taieb, Antti Sorjamaa and Gianluca Bontempi (2010) Multiple-output modeling for multi-step-ahead time series forecasting. Neurocomputing, 73(10-12):1950–1957, 2010.. Abstract Online


  • Souhaib Ben Taieb, Gianluca Bontempi, Antti Sorjamaa and Amaury Lendasse (2009) Long-Term Prediction of Time Series by combining Direct and MIMO Strategies. IEEE International Joint Conference on Neural Networks (IJCNN), 2009.. Abstract Online