Cover Image

Graph Neural Networks for Electricity Load Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Campagne, Eloi, Amara-Ouali, Yvenn, Goude, Yannig, Zehavi, Itai, Kalogeratos, Argyris
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging Graph Neural Networks to Forecast Electricity Consumption
by: Campagne, Eloi, et al.
Published: (2024)

Cascaded Transfer: Learning Many Tasks under Budget Constraints
by: Campagne, Eloi, et al.
Published: (2026)

Spatio-temporal modelling of electric vehicle charging demand
by: Bouaachra, Kaoutar, et al.
Published: (2026)

Conformal Prediction for Hierarchical Data
by: Principato, Guillaume, et al.
Published: (2024)

Achieving Skilled and Reliable Daily Probabilistic Forecasts of Wind Power at Subseasonal-to-Seasonal Timescales over France
by: Lindas, Eloi, et al.
Published: (2025)

Dual-Criterion Curriculum Learning: Application to Temporal Data
by: Abel, Gaspard, et al.
Published: (2026)

Towards Accurate Forecasting of Renewable Energy : Building Datasets and Benchmarking Machine Learning Models for Solar and Wind Power in France
by: Lindas, Eloi, et al.
Published: (2025)

Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge
by: Amara-Ouali, Yvenn, et al.
Published: (2023)

Forecasting time series with constraints
by: Doumèche, Nathan, et al.
Published: (2025)

Enhancing LIME using Neural Decision Trees
by: Bouyahia, Mohamed Aymen, et al.
Published: (2026)

Hedging Memory Horizons for Non-Stationary Prediction via Online Aggregation
by: Wang, Yutong, et al.
Published: (2026)

Multi-view diffusion geometry using intertwined diffusion trajectories
by: Debaussart-Joniec, Gwendal, et al.
Published: (2025)

Parametrized Power-Iteration Clustering for Directed Graphs
by: Debaussart-Joniec, Gwendal, et al.
Published: (2022)

Stein Boltzmann Sampling: A Variational Approach for Global Optimization
by: Serré, Gaëtan, et al.
Published: (2024)

Generalized Dirichlet Energy and Graph Laplacians for Clustering Directed and Undirected Graphs
by: Sevi, Harry, et al.
Published: (2022)

Collaborative non-parametric two-sample testing
by: de la Concha, Alejandro, et al.
Published: (2024)

Collaborative likelihood-ratio estimation over graphs
by: de la Concha, Alejandro, et al.
Published: (2022)

Uncovering Social Network Activity Using Joint User and Topic Interaction
by: Abel, Gaspard, et al.
Published: (2025)

Offline detection of change-points in the mean for stationary graph signals
by: de la Concha, Alejandro, et al.
Published: (2020)

Generative Unsupervised Downscaling of Climate Models via Domain Alignment: Application to Wind Fields
by: Keisler, Julie, et al.
Published: (2026)

SerpentFlow: Generative Unpaired Domain Alignment via Shared-Structure Decomposition
by: Keisler, Julie, et al.
Published: (2026)

Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints
by: Singer, Gabriel, et al.
Published: (2026)

Convergence of SGD for Training Neural Networks with Sliced Wasserstein Losses
by: Tanguy, Eloi
Published: (2023)

Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning
by: Rahman, Ratun, et al.
Published: (2025)

Adaptive Physics-Guided Neural Network
by: Shulman, David, et al.
Published: (2024)

Parametrizing Convex Sets Using Sublinear Neural Networks
by: Martinet, Eloi
Published: (2026)

Recurrent Neural Networks with Linear Structures for Electricity Price Forecasting
by: Amor, Souhir Ben, et al.
Published: (2025)

DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model
by: Wang, Zhixian, et al.
Published: (2023)

Probabilistic Demand Forecasting with Graph Neural Networks
by: Kozodoi, Nikita, et al.
Published: (2024)

Fourier-Enhanced Recurrent Neural Networks for Electrical Load Time Series Downscaling
by: Chen, Qi, et al.
Published: (2025)

BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network
by: Liu, Yongzheng, et al.
Published: (2025)

Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
by: Oskarsson, Joel, et al.
Published: (2024)

ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks
by: Cai, Wanlin, et al.
Published: (2024)

Load Forecasting on A Highly Sparse Electrical Load Dataset Using Gaussian Interpolation
by: Biswas, Chinmoy, et al.
Published: (2025)

Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning
by: Mahtout, Btissame El, et al.
Published: (2026)

Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
by: Kyriakopoulos, Iason, et al.
Published: (2025)

Graph Neural Networks in Wind Power Forecasting
by: Castellano, Javier, et al.
Published: (2025)

Meshless Shape Optimization using Neural Networks and Partial Differential Equations on Graphs
by: Martinet, Eloi, et al.
Published: (2025)

Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall
by: Bülte, Christopher, et al.
Published: (2025)

Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting
by: Lee, Sanghyun, et al.
Published: (2024)