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Generative anomaly detection: a comprehensive review of modeling principles, advances, and future opportunities.

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Title: Generative anomaly detection: a comprehensive review of modeling principles, advances, and future opportunities.
Authors: Zhu, Jiaqi1, jiaqi_zhu@bit.edu.cn, Fan, Yunfeng2, yunfeng.fan@connect.polyu.hk, Han, Geng1, 3120215446@bit.edu.cn, Shi, Xiang3, shi-xiang@tsinghua.edu.cn, Deng, Fang1, dengfang@bit.edu.cn, Chen, Jie1,4, chenjie@bit.edu.cn
Source: Artificial Intelligence Review; Sep2026, Vol. 59 Issue 9, p1-74, 74p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Generative anomaly detection: a comprehensive review of modeling principles, advances, and future opportunities.
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      – Type: doi
        Value: 10.1007/s10462-026-11591-w
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        Text: English
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        PageCount: 74
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      – TitleFull: Generative anomaly detection: a comprehensive review of modeling principles, advances, and future opportunities.
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              M: 09
              Text: Sep2026
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              Y: 2026
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