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A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences

Neural Information Processing Systems

Such causal graphs delineate the relations among alarms and can significantly aid engineers in identifying and rectifying faults. However, existing methods either ignore the topological relationships among devices or suffer from relatively low scalability and efficiency, failing to deliver high-quality responses in a timely manner.