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Joseph de Vilmarest
Joseph de Vilmarest
Viking Conseil
Adresă de e-mail confirmată pe vikingconseil.fr - Pagina de pornire
Titlu
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Adaptive methods for short-term electricity load forecasting during COVID-19 lockdown in France
D Obst, J De Vilmarest, Y Goude
IEEE transactions on power systems 36 (5), 4754-4763, 2021
1012021
State-space models for online post-covid electricity load forecasting competition
J De Vilmarest, Y Goude
IEEE Open Access Journal of Power and Energy 9, 192-201, 2022
38*2022
Adaptive probabilistic forecasting of electricity (net-) load
J de Vilmarest, J Browell, M Fasiolo, Y Goude, O Wintenberger
IEEE Transactions on Power Systems 39 (2), 4154-4163, 2023
112023
Stochastic online optimization using kalman recursion
J De Vilmarest, O Wintenberger
Journal of Machine Learning Research 22 (223), 1-55, 2021
92021
Viking: variational Bayesian variance tracking
J Vilmarest, O Wintenberger
Statistical Inference for Stochastic Processes 27 (3), 839-860, 2024
7*2024
Modèles espace-état pour la prévision de séries temporelles. Application aux marchés électriques
J de Vilmarest
Sorbonne université, 2022
3*2022
Viking: Variational bayesian variance tracking winning a post-covid day-ahead electricity load forecasting competition
J de Vilmarest, Y Goude, O Wintenberger
TSW-ICML2021_paper_15. pdf, 2021
32021
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models
G Lambert, B Hamrouche, J De Vilmarest
Scientific Reports 13 (1), 15784, 2023
22023
An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition
J de Vilmarest, N Werge
International Journal of Forecasting, 2024
12024
Adaptive time series forecasting with markovian variance switching
B Abélès, J De Vilmarest, O Wintemberger
arXiv preprint arXiv:2402.14684, 2024
2024
Online Learning Approach for Survival Analysis
C Fernandez, P Gaillard, J De Vilmarest, O Wintenberger
arXiv preprint arXiv:2402.05145, 2024
2024
Logarithmic Regret for parameter-free Online Logistic Regression
J De Vilmarest, O Wintenberger
arXiv preprint arXiv:1902.09803, 2019
2019
Day-ahead electricity demand forecasting: post-codid paradigm (report team 4)
J de Vilmarest, Y Goude
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