ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks

30 September 2020

Papers citing "ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks"

9 / 9 papers shown

Title
A Graph Encoder-Decoder Network for Unsupervised Anomaly Detection Mahsa Mesgaran A. Ben Hamza 31 3 0 15 Aug 2023
Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection Hezhe Qiao Guansong Pang 19 24 0 29 May 2023
A Novel Self-Supervised Learning-Based Anomaly Node Detection Method Based on an Autoencoder in Wireless Sensor Networks Miao Ye Qinghao Zhang Xingsi Xue Yong Wang Qiuxiang Jiang Hongbing Qiu 13 0 0 26 Dec 2022
ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness Jingcan Duan Bin Xiao Siwei Wang Haifang Zhou Xinwang Liu AI4TS 22 10 0 28 Nov 2022
A Novel Anomaly Detection Method for Multimodal WSN Data Flow via a Dynamic Graph Neural Network Qinghao Zhang Miao Ye Hongbing Qiu Yong Wang Xiaofang Deng 22 13 0 19 Feb 2022
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning Xiaoxiao Ma Jia Wu Shan Xue Jian Yang Chuan Zhou Quan Z. Sheng Hui Xiong Leman Akoglu GNN AI4TS 43 538 0 14 Jun 2021
Pseudo-Riemannian Graph Convolutional Networks Bo Xiong Shichao Zhu Nico Potyka Shirui Pan Chuan Zhou Steffen Staab GNN 38 28 0 06 Jun 2021
Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks Tianjin Huang Yulong Pei Vlado Menkovski Mykola Pechenizkiy 27 32 0 16 Apr 2021
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 279 1,944 0 09 Jun 2018