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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

State-Space Models for Online Post-Covid Electricity Load Forecasting Competition
Joseph de Vilmarest, Yannig Goude
IEEE Open Access Journal of Power and Energy (2022) Vol. 9, pp. 192-201
Open Access | Times Cited: 19

Showing 19 citing articles:

Efficient mid-term forecasting of hourly electricity load using generalized additive models
Monika Zimmermann, Florian Ziel
Applied Energy (2025) Vol. 388, pp. 125444-125444
Closed Access
Hierarchical transfer learning with applications to electricity load forecasting
Anestis Antoniadis, Solenne Gaucher, Yannig Goude
International Journal of Forecasting (2023) Vol. 40, Iss. 2, pp. 641-660
Open Access | Times Cited: 12
A transfer learning-based hybrid model with LightGBM for smart grid short-term energy load prediction
Sarita Simaiya, Mamta Dahiya, Shilpi Tomar, et al.
Energy Exploration & Exploitation (2024) Vol. 42, Iss. 5, pp. 1853-1876
Open Access | Times Cited: 2
Optimal Selection of Weather Stations for Electric Load Forecasting
Eduardo Caro, Jesús Juan, Shadi Nouhitehrani
IEEE Access (2023) Vol. 11, pp. 42981-42990
Open Access | Times Cited: 6
Adaptive Probabilistic Forecasting of Electricity (Net-)Load
Joseph de Vilmarest, Jethro Browell, Matteo Fasiolo, et al.
IEEE Transactions on Power Systems (2023) Vol. 39, Iss. 2, pp. 4154-4163
Open Access | Times Cited: 5
Efficient Mid-Term Forecasting of Hourly Electricity Load Using Generalized Additive Models
Monika Zimmermann, Florian Ziel
(2024)
Open Access | Times Cited: 1
Kalman recursions Aggregated Online
Eric Adjakossa, Yannig Goude, Olivier Wintenberger
Statistical Papers (2023) Vol. 65, Iss. 2, pp. 909-944
Closed Access | Times Cited: 4
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models
G. Lambert, Bachir Hamrouche, Joseph de Vilmarest
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 2
Viking: variational Bayesian variance tracking
Joseph de Vilmarest, Olivier Wintenberger
Statistical Inference for Stochastic Processes (2024) Vol. 27, Iss. 3, pp. 839-860
Closed Access
An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition
Joseph de Vilmarest, Nicklas Werge
International Journal of Forecasting (2024)
Open Access
FORECASTING ECONOMIC TIME SERIES WITH EXOGENOUS VARIA-BLES: OPPORTUNITIES IN COMPUTATIONAL PARAMETRIZATION TECHNIQUES FOR SUPPORTING PUBLIC DEVELOPMENT POLICIES
Rafael Diniz Toscano de Lima, Sérgio Murilo Maciel Fernandes, Sidney Marlon Lopes de Lima, et al.
Revista Políticas Públicas & Cidades (2024) Vol. 13, Iss. 2, pp. e899-e899
Open Access
Spatial Meteorological, Socio-Economic, and Political Risks in Probabilistic Electricity Demand Forecasting
Monika Zimmermann, Florian Ziel
(2024)
Closed Access
Residual Analysis-Based Model Improvement for State Space Models With Nonlinear Responses
Xun Shen, Jiancang Zhuang
IEEE Transactions on Emerging Topics in Computational Intelligence (2024) Vol. 8, Iss. 2, pp. 1728-1743
Closed Access
Adaptive Forecasting of Extreme Electricity Load
Omar Himych, Amaury Durand, Yannig Goude
Lecture notes in computer science (2024), pp. 201-215
Closed Access
A Hybrid Model for Short-Term Energy Load Prediction Based on Transfer Learning with LightGBM for Smart Grids in Smart Energy Systems
Surjeet Dalal, Umesh Kumar Lilhore, Bijeta Seth, et al.
Journal of Urban Technology (2024), pp. 1-27
Closed Access
A Hybrid Deep Neural Network Architecture for Day-Ahead Electricity Forecasting: Post-COVID Paradigm
Neilson Luniere Vilaça, M. G. F. Costa, Cícero Ferreira Fernandes Costa Filho
Energies (2023) Vol. 16, Iss. 8, pp. 3546-3546
Open Access | Times Cited: 1
Human spatial dynamics for electricity demand forecasting: the case of France during the 2022 energy crisis
Nathan Doumèche, Yann Allioux, Yannig Goude, et al.
arXiv (Cornell University) (2023)
Open Access
Short term demand forecasting using polynomial ARX models based on least squares methods
Takehito Azuma, Kei Kikuchi
(2023), pp. 1-4
Closed Access
Editorial Special Section on COVID-19 Impact on Electrical Grid Operation: Analysis and Mitigation
Chongqing Kang, Jethro Browell, Mostafa Farrokhabadi, et al.
IEEE Open Access Journal of Power and Energy (2022) Vol. 9, pp. 183-184
Open Access
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