Mul-GAD: a semi-supervised graph anomaly detection framework via aggregating multi-view information

11 December 2022

Papers citing "Mul-GAD: a semi-supervised graph anomaly detection framework via aggregating multi-view information"

7 / 7 papers shown

Title
UniGAD: Unifying Multi-level Graph Anomaly Detection Yiqing Lin Jianheng Tang Chenyi Zi Haihong Zhao Yuan Yao Jia Li 24 0 0 10 Nov 2024
Graph Pre-Training Models Are Strong Anomaly Detectors Jiashun Cheng Zinan Zheng Yang Liu Jianheng Tang H. Wang Yu Rong Jia Li Fugee Tsung 24 1 0 24 Oct 2024
Deep Graph Anomaly Detection: A Survey and New Perspectives Hezhe Qiao Hanghang Tong Bo An Irwin King Charu Aggarwal Guansong Pang 27 5 0 16 Sep 2024
Towards Fair Graph Anomaly Detection: Problem, New Datasets, and Evaluation Neng Kai Nigel Neo Yeon-Chang Lee Yiqiao Jin Sang-Wook Kim Srijan Kumar 36 4 0 25 Feb 2024
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection Jianheng Tang Fengrui Hua Zi-Chao Gao P. Zhao Jia Li 14 23 0 21 Jun 2023
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction Amit Roy Juan Shu Jia Li Carl Yang Olivier Elshocht Jeroen Smeets P. Li 26 40 0 02 Jun 2023
Rethinking Graph Neural Networks for Anomaly Detection Jianheng Tang Jiajin Li Zi-Chao Gao Jia Li 67 193 0 31 May 2022