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Generating synthetic power-grid scenarios that are both operationally feasible and statistically accurate could revolutionize planning and resilience assessments in power systems.
Foundation models can now predict power grid dynamics with zero-shot generalization, opening the door to faster, more reliable grid management.
Standard image segmentation techniques undermine the theoretical guarantees of hierarchical Shapley explanations, but a new segmentation method restores consistency and boosts performance.
