Guansong Pang

Nov 26, 2024 | arxiv.org | Guansong Pang |Hezhe Qiao |Yuan Gao |Hui Yan

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Apr 14, 2024 | towardsdatascience.com | Guansong Pang

Generalist Anomaly Detection (GAD) aims to train one single detection model that can generalize to detect anomalies in diverse datasets from different application domains without any further training on the target data. Work to be published at CVPR 2024 [1].

Mar 11, 2024 | arxiv.org | Guansong Pang

May 29, 2023 | arxiv.org | Guansong Pang

[Submitted on 29 May 2023 ( v1 ), last revised 4 Apr 2024 (this version, v5)] Title:Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection View a PDF of the paper titled Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection, by Hezhe Qiao and Guansong Pang View PDF HTML (experimental) Abstract:We reveal a one-class homophily phenomenon, which is one prevalent property we find empirically in real-world graph anomaly...

Apr 23, 2023 | arxiv.org | Guansong Pang |Yijie Wang |Yongjun Wang

arXiv:2206.06602 (cs) [Submitted on 14 Jun 2022 (v1), last revised 9 Jun 2023 (this version, v4)] Download a PDF of the paper titled Deep Isolation Forest for Anomaly Detection, by Hongzuo Xu and Guansong Pang and Yijie Wang and Yongjun Wang Download PDF Submission history From: Hongzuo Xu [ view email] [v1] Tue, 14 Jun 2022 05:47:07 UTC (515 KB) [v2] Thu, 29 Sep 2022 02:50:25 UTC (726 KB) [v3] Sun, 23 Apr 2023 04:45:05 UTC (931 KB) [v4] Fri, 9 Jun 2023 01:19:55 UTC (4,952 KB) Bibliographic...