ADAEN: Adaptive Diffusion Adversarial Evolutionary Network for Unsupervised Anomaly Detection in Tabular Data

Existing unsupervised anomaly detection methods suffer from insufficient parameter precision, poor robustness to noise, and limited generalization capability. To address these issues, this paper proposes an Adaptive Diffusion Adversarial Evolutionary Network (ADAEN) for unsupervised anomaly detectio...

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Bibliografiske detaljer

Principais autores:	Yong Lu, Sen Wang, Lingjun Kong, Wenju Wang
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2026-01-01
Serier:	Applied System Innovation
Fag:	unsupervised anomaly detection adversarial networks diffusion model Wasserstein distance tabular data transformer encoder
Online adgang:	https://www.mdpi.com/2571-5577/9/2/36
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