A significant amount of fraudulent activity tends to go unreported in reality, one of the major focuses for our team recently has been to develop robust GNNs that can perform anomaly detection on noisily labeled graphs. Noisily labeled anomalous data can reduce the model performance as it learns incorrect patterns during training, cause the model […]
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