Generative and Contrastive Self-Supervised Learning for Graph Anomaly
Detection

Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection

23 August 2021

Ming Jin

Yi-Ping Phoebe Chen

Papers citing "Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection"

7 / 7 papers shown

Title
GRAM: An Interpretable Approach for Graph Anomaly Detection using Gradient Attention Maps Yifei Yang Peng Wang Xiaofan He Dongmian Zou 14 5 0 10 Nov 2023
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation Shuang Zhou Xiao Shi Huang Ninghao Liu Huachi Zhou F. Chung Longhai Huang 28 22 0 18 Jun 2023
Decoupling anomaly discrimination and representation learning: self-supervised learning for anomaly detection on attributed graph Yanming Hu Chuan Chen Bowen Deng Yujing Lai Hao Lin Zibin Zheng Jing Bian 27 1 0 11 Apr 2023
Abnormal Event Detection via Hypergraph Contrastive Learning Bo Yan Cheng Yang Chuan Shi Jiawei Liu Xiaochen Wang 14 3 0 02 Apr 2023
Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method Yihong Huang Liping Wang Fan Zhang Xuemin Lin 23 19 0 24 Oct 2022
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning Di Jin Zhizhi Yu Pengfei Jiao Shirui Pan Dongxiao He Jia Wu Philip S. Yu Weixiong Zhang GNN 111 266 0 03 Jan 2021
Graph Geometry Interaction Learning Shichao Zhu Shirui Pan Chuan Zhou Jia Wu Yanan Cao Bin Wang 53 90 0 23 Oct 2020