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cs.AI2025
Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories
Pantelis Dogoulis, Fabien Bernier, Félix Fourreau +2
Many real-world machine learning tasks require outputs that satisfy hard constraints, such as physical conservation laws, structured dependencies in graphs, or column-level relatio…
cs.AI2025
KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections
Pantelis Dogoulis, Karim Tit, Maxime Cordy
In the modern context of power systems, rapid, scalable, and physically plausible power flow predictions are essential for ensuring the grid's safe and efficient operation. While t…