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Physics-Aware Random Walk Fingerprints for Scalable Power Grid Graph Classification

Anwar, Adnan
arXiv (All) · Papers
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systems-and-control
Recent benchmarks such as PowerGraph provide large collections of power-grid graphs for cascading-failure classification. Graph neural networks (GNNs) achieve strong predictive performance on this task, but typically require end-to-end training and model-specific tuning, while their latent represent
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