Souhaib Ben Taieb

According to our database, Souhaib Ben Taieb authored at least 26 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Distribution-free conformal joint prediction regions for neural marked temporal point processes.

Victor Dheur, Tanguy Bosser, Rafael Izbicki, Souhaib Ben Taieb

Mach. Learn., September, 2024

Anomaly detection with semi-supervised classification based on risk estimators.

Le Thi Khanh Hien, Sukanya Patra, Souhaib Ben Taieb

Trans. Mach. Learn. Res., 2024

Preventing Conflicting Gradients in Neural Marked Temporal Point Processes.

Tanguy Bosser, Souhaib Ben Taieb

CoRR, 2024

Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection.

Sukanya Patra, Souhaib Ben Taieb

CoRR, 2024

Detecting Abnormal Operations in Concentrated Solar Power Plants from Irregular Sequences of Thermal Images.

Sukanya Patra, Nicolas Sournac, Souhaib Ben Taieb

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Probabilistic Calibration by Design for Neural Network Regression.

Victor Dheur, Souhaib Ben Taieb

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

On the Predictive Accuracy of Neural Temporal Point Process Models for Continuous-time Event Data.

Tanguy Bosser, Souhaib Ben Taieb

Trans. Mach. Learn. Res., 2023

A Large-Scale Study of Probabilistic Calibration in Neural Network Regression.

Victor Dheur, Souhaib Ben Taieb

Proceedings of the International Conference on Machine Learning, 2023

Anomaly detection in irregular image sequences for concentrated solar power plants.

Sukanya Patra, Le Thi Khanh Hien, Souhaib Ben Taieb

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Revisiting the Mark Conditional Independence Assumption in Neural Marked Temporal Point Processes.

Tanguy Bosser, Souhaib Ben Taieb

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2022

Learning Quantile Functions for Temporal Point Processes with Recurrent Neural Splines.

Souhaib Ben Taieb

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020

Forecasting: theory and practice.

Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Souhaib Ben Taieb, Christoph Bergmeir, Ricardo J. Bessa, Jakub Bijak, John E. Boylan, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Joanne Ellison, Piotr Fiszeder, Philip Hans Franses, David T. Frazier, Michael Gilliland, Mustafa Sinan Gönül, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li

CoRR, 2020

2019

Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions.

Souhaib Ben Taieb, Bonsoo Koo

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2017

Coherent Probabilistic Forecasts for Hierarchical Time Series.

Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman

Proceedings of the 34th International Conference on Machine Learning, 2017

Regularization in Hierarchical Time Series Forecasting with Application to Electricity Smart Meter Data.

Souhaib Ben Taieb, Jiafan Yu, Mateus Neves Barreto, Ram Rajagopal

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression.

Souhaib Ben Taieb, Raphaël Huser, Rob J. Hyndman, Marc G. Genton

IEEE Trans. Smart Grid, 2016

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

Souhaib Ben Taieb, Amir F. Atiya

IEEE Trans. Neural Networks Learn. Syst., 2016

Sparse and Smooth Adjustments for Coherent Forecasts in Temporal Aggregation of Time Series.

Souhaib Ben Taieb

Proceedings of the NIPS 2016 Time Series Workshop, 2016

2015

Decentralized Energy and Power Estimation in Solar-Powered Wireless Sensor Networks.

Ahmad H. Dehwah, Souhaib Ben Taieb, Jeff S. Shamma, Christian G. Claudel

Proceedings of the 2015 International Conference on Distributed Computing in Sensor Systems, 2015

2014

Boosting multi-step autoregressive forecasts.

Souhaib Ben Taieb, Rob J. Hyndman

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

A Time Series Approach for Profiling Attack.

Liran Lerman, Gianluca Bontempi, Souhaib Ben Taieb, Olivier Markowitch

Proceedings of the Security, Privacy, and Applied Cryptography Engineering, 2013

2012

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition.

Souhaib Ben Taieb, Gianluca Bontempi, Amir F. Atiya, Antti Sorjamaa

Expert Syst. Appl., 2012

Machine Learning Strategies for Time Series Forecasting.

Gianluca Bontempi, Souhaib Ben Taieb, Yann-Aël Le Borgne

Proceedings of the Business Intelligence - Second European Summer School, 2012

2011

Recursive Multi-step Time Series Forecasting by Perturbing Data.

Souhaib Ben Taieb, Gianluca Bontempi

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

Multiple-output modeling for multi-step-ahead time series forecasting.

Souhaib Ben Taieb, Antti Sorjamaa, Gianluca Bontempi

Neurocomputing, 2010

2009

Long-term prediction of time series by combining direct and MIMO strategies.

Souhaib Ben Taieb, Gianluca Bontempi, Antti Sorjamaa, Amaury Lendasse

Proceedings of the International Joint Conference on Neural Networks, 2009