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cs.LG2026
Benchmarking Graph Neural Networks for AC Power Flow: The Role of Inductive Biases and Physical Constraints
Federico Clerici, Ferran Bohigas-Daranas, Hamid Latif-Martínez +3
Fast and accurate models for AC power flow (ACPF) are increasingly important as modern electrical grids require more frequent system analyses. Graph neural networks (GNNs) naturall…
cs.LG2026
Power Flow Feasibility Assessment Using Variational Graph Autoencoders
Ferran Bohigas-Daranas, Hamid Latif-Martinez, Eduardo Prieto-Araujo +2
Data-driven methods, including graph neural networks, have been studied for accelerating power flow calculations in recent years, but very little attention has been paid to the sol…