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The DTD-VAE framework achieves performance gains of 3.2%-4.86% in ROC-AUC and 6.41%-9.71% in Accuracy Ratio compared to existing methods on real-world datasets
Extensive experiments on six real-world datasets demonstrate that the proposed framework consistently outperforms existing methods, achieving performance gains of 3.2%-4.86% in ROC-AUC and 6.41%-9.71% in Accuracy Ratio.
Machine Learning (Statistics)29 Aug 2026