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Xu, X., , Chen, Y., Goude, Y., Yao, Q. (2021) Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression, accepted in Applied Energies.
Amara-Ouali, Y., Goude, Y., Massart, P., Poggi, J. M., & Yan, H. (2021). A review of electric vehicle load open data and models. Energies, 14(8), 2233.
Amato, U., Antoniadis, A., De Feis, I., Goude, Y., & Lagache, A. (2021). Forecasting high resolution electricity demand data with additive models including smooth and jagged components. International Journal of Forecasting, 37(1), 171-185.
Capezza, C., Palumbo, B., Goude, Y., Wood, S. N., & Fasiolo, M. (2021). Additive stacking for disaggregate electricity demand forecasting. The Annals of Applied Statistics, 15(2), 727-746.
Fasiolo, M., Wood, S. N., Zaffran, M., Nedellec, R., & Goude, Y. (2020). Fast calibrated additive quantile regression. Journal of the American Statistical Association, 1-11.
Fasiolo, M., Nedellec, R., Goude, Y., & Wood, S. N. (2020). Scalable visualization methods for modern generalized additive models. Journal of computational and Graphical Statistics, 29(1), 78-86.
Devijver, E., Goude, Y., & Poggi, J. M. (2020). Clustering electricity consumers using high‐dimensional regression mixture models. Applied Stochastic Models in Business and Industry, 36(1), 159-177.
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Auder, B.; Cugliari, J.; Goude, Y. & Poggi, J.-M. Scalable Clustering of Individual Electrical Curves for Profiling and Bottom-Up Forecasting Energies, 2018, 11.
Mei, J.; Castro, Y. D.; Goude, Y.; Azaïs, J. & Hebrail, G. Nonnegative matrix factorization with side information for time series recovery and prediction IEEE Transactions on Knowledge and Data Engineering, 2018, 1-1.
Amato, U.; Antoniadis, A.; De Feis, I. & Goude, Y. Estimation and group variable selection for additive partial linear models with wavelets and splines South African Statistical Journal, South African Statistical Association (SASA), 2017, 51, 235-272.
Gaillard, P.; Goude, Y. & Nedellec, R. Additive models and robust aggregation for GEFCom2014 probabilistic electric load and electricity price forecasting International Journal of Forecasting, Elsevier, 2016, 32, 1038-1050.
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Thouvenot, V.; Pichavant, A.; Goude, Y.; Antoniadis, A. & Poggi, J. M. Electricity Forecasting Using Multi-Stage Estimators of Nonlinear Additive Models IEEE Transactions on Power Systems, 2016, 31, 3665-3673.
Cho, H.; Goude, Y.; Brossat, X. & Yao, Q. Antoniadis, A.; Poggi, J.-M. & Brossat, X. (Eds.) Modelling and Forecasting Daily Electricity Load via Curve Linear Regression Modeling and Stochastic Learning for Forecasting in High Dimensions, Springer International Publishing, 2015, 217, 35-54.
Gaillard, P. & Goude, Y. Antoniadis, A.; Poggi, J.-M. & Brossat, X. (Eds.) Forecasting Electricity Consumption by Aggregating Experts; How to Design a Good Set of Experts Modeling and Stochastic Learning for Forecasting in High Dimensions, Springer International Publishing, 2015, 217, 95-115.
Pompey, P.; Bondu, A.; Goude, Y. & Sinn, M. Antoniadis, A.; Poggi, J.-M. & Brossat, X. (Eds.) Massive-Scale Simulation of Electrical Load in Smart Grids Using Generalized Additive Models Modeling and Stochastic Learning for Forecasting in High Dimensions, Springer International Publishing, 2015, 217, 193-212.
Wood, S. N.; Goude, Y. & Shaw, S. Generalized additive models for large data sets Journal of the Royal Statistical Society: Series C (Applied Statistics), 2015, 64, 139-155.
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Nedellec, R.; Cugliari, J. & Goude, Y. GEFCom2012: Electric load forecasting and backcasting with semi-parametric models International Journal of Forecasting, 2014, 30, 375 - 381.
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Devaine, M.; Gaillard, P.; Goude, Y. & Stoltz, G. Forecasting electricity consumption by aggregating specialized experts - A review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions Machine Learning, 2013, 90, 231-260.
Enbis workshop Interpretability for Industry 4.0, Pillar 2: Interpretability via additive models 12-13th July 2021, Adaptive Methods for Short-Term Electricity Load Forecasting During COVID-19 Lockdowns in France, from GAM to aggregation of experts, are we still interpretable? slides
Mei, J.; De Castro, Y.; Goude, Y. & Hébrail, G. Precup, D. & Teh, Y. W. (Eds.) Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates Proceedings of the 34th International Conference on Machine Learning, PMLR, 2017, 70, 2382-2390.
Pierrot, A.; Goude, Y. & Yao, Q. Curve Linear Regression with clr The R User Conference, useR! 2017 July 4-7 2017 Brussels, Belgium, 2017, 33.
Mei, J.; Hebrail, G.; Goude, Y. & Kong, N. Spatial Estimation of Electricity Consumption Using Socio-demographic Information APPEEC, IEEE PES APPEEC 2016, 2016.
Cugliari, J.; Goude, Y. & Poggi, J. M. Disaggregated electricity forecasting using wavelet-based clustering of individual consumers 2016 IEEE International Energy Conference (ENERGYCON), 2016, 1-6.
Ba, A.; Sinn, M.; Goude, Y. & Pompey, P. Bartlett, P.; Pereira, F.; Burges, C.; Bottou, L. & Weinberger, K. (Eds.) Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting Advances in Neural Information Processing Systems 25, 2012, 2519-2527
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Amara-Ouali, Y., Goude, Y., Massart, P., Poggi, J. M., & Yan, H. (2020). A review of electric vehicle load open data and models.
Obst, D., de Vilmarest, J., & Goude, Y. (2020). Adaptive Methods for Short-Term Electricity Load Forecasting During COVID-19 Lockdown in France. arXiv preprint arXiv:2009.06527.
Xu, X., Chen, Y., Goude, Y., & Yao, Q. (2020). Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression. arXiv preprint arXiv:2009.01595.
Adjakossa, E., Goude, Y., & Wintenberger, O. (2020). Kalman Recursions Aggregated Online. arXiv preprint arXiv:2002.12173.
Obst, D., Ghattas, B., Claudel, S., Cugliari, J., Goude, Y., & Oppenheim, G. (2019). Textual Data for Time Series Forecasting. arXiv preprint arXiv:1910.12618.
Brégère, M., Goude Y., Gaillard, P. and Gilles Stoltz, Target tracking for contextual bandits: Application to demand side management, 2019.
Mei, J.; De Castro, Y.; Goude, Y.; Aza, J.-M. & Hébrail, G. Nonnegative matrix factorization with side information for time series recovery and prediction arXiv preprint arXiv:1709.06320, 2017.
Fasiolo, M.; Goude, Y.; Nedellec, R. & Wood, S. N. Fast calibrated additive quantile regression arXiv preprint arXiv:1707.03307, 2017.
Mei, J., De Castro Y., Goude, Y. and Hebrail, G., Recovering multiple time series from a few temporally aggregated measurements, submitted to ICASSP, 2016.
Devijver, E., Goude, Y. and Poggi, J.-M., Clustering electricity consumers using highdimensional regression mixture models, submitted to Applied Stochastic Models in Business and Industry, 2016.
Antoniadis, A.; Goude, Y.; Poggi, J.-M. & Thouvenot, V. Sélection de variables dans les modèles additifs avec des estimateurs en plusieurs étapes Université d'Orsay ; EDF R&D ; Université Joseph Fourier ; Université Cap Town ; Université Paris Descartes, 2015