Models regimes in temporal graphs as geodesic trajectories and detects changes as drifts from estimated geodesics, outperforming baselines on synthetic data and showing better alignment with external events on COVID mobility data.
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning,
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Geodesics of Dynamic Graphs for Regime Change Detection
Models regimes in temporal graphs as geodesic trajectories and detects changes as drifts from estimated geodesics, outperforming baselines on synthetic data and showing better alignment with external events on COVID mobility data.