PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection

18 October 2023

Papers citing "PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection"

8 / 8 papers shown

Title
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs Jiazhen Chen Sichao Fu Zheng Ma M. Feng T. Wirjanto Qinmu Peng 37 0 0 25 Jan 2025
MEATRD: Multimodal Anomalous Tissue Region Detection Enhanced with Spatial Transcriptomics Kaichen Xu Qilong Wu Yan Lu Yinan Zheng W. Li Xingjie Tang Jun Wang Xiaobo Sun 69 0 0 14 Dec 2024
Towards Cross-domain Few-shot Graph Anomaly Detection Jiazhen Chen Sichao Fu Zhibin Zhang Zheng Ma M. Feng T. Wirjanto Qinmu Peng 20 2 0 11 Oct 2024
Deep Graph Anomaly Detection: A Survey and New Perspectives Hezhe Qiao Hanghang Tong Bo An Irwin King Charu Aggarwal Guansong Pang 21 5 0 16 Sep 2024
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark Yili Wang Yixin Liu Xu Shen Chenyu Li Kaize Ding Rui Miao Ying Wang Shirui Pan Xin Wang 24 6 0 21 Jun 2024
SmoothGNN: Smoothing-based GNN for Unsupervised Node Anomaly Detection Xiangyu Dong Xing Zhang Yanni Sun Lei Chen Mingxuan Yuan Sibo Wang 16 1 0 27 May 2024
ARC: A Generalist Graph Anomaly Detector with In-Context Learning Yixin Liu Shiyuan Li Yu Zheng Qingfeng Chen Chengqi Zhang Shirui Pan 25 9 0 27 May 2024
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization Xiaotian Han Tong Zhao Yozen Liu Xia Hu Neil Shah GNN 25 36 0 30 Sep 2022