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Islamic University of Technology
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RINSE achieves state-of-the-art performance in zero-shot graph anomaly detection by effectively estimating target normality without requiring any target labels or gradients.
Incorporating spectral structural priors into uncertain knowledge graph completion can dramatically enhance prediction accuracy and training stability without adding extra parameters.
