Proposes DMD and SINDy as new explainability tools for STGNNs, showing they recover interpretable features like infection times and nodes on semi-synthetic data and action-relevant body parts on real motion data.
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Interpreting Temporal Graph Neural Networks with Koopman Theory
Proposes DMD and SINDy as new explainability tools for STGNNs, showing they recover interpretable features like infection times and nodes on semi-synthetic data and action-relevant body parts on real motion data.