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Graph Anomaly Detection (GAD) has recently become a hot research spot due to its practicability and theoretical value.
Birds of a feather: Homophily in social networks
Miller McPherson, Lynn Smith-Lovin, and James M Cook · 2001
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Scan: A structural clustering algorithm for networks
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, and Thomas AJ Schweiger · 2007
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Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor · 2008
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Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Social influence analysis in large-scale networks
Jie Tang, Jimeng Sun, Chi Wang, and Zi Yang · 2009
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Node classification in social networks
Smriti Bhagat, Graham Cormode, and S Muthukrishnan · 2011
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mice: Multivariate imputation by chained equations in r
Stef Van Buuren and Karin Groothuis-Oudshoorn · 2011
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Time-varying graphs and dynamic networks
Arnaud Casteigts, Paola Flocchini, Walter Quattrociocchi, and Nicola Santoro · 2012
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From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews
Julian John McAuley and Jure Leskovec · 2013
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What yelp fake review filter might be doing?
Arjun Mukherjee, Vivek Venkataraman, Bing Liu, and Natalie Glance · 2013
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Statistical selection of congruent subspaces for mining attributed graphs
Patricia Iglesias Sánchez, Emmanuel Müller, Fabian Laforet, Fabian Keller, and Klemens Böhm · 2013
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Reciprocal versus parasocial relationships in online social networks
Neil Zhenqiang Gong and Wenchang Xu · 2014
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Anomaly detection using autoencoders with nonlinear dimensionality reduction
Mayu Sakurada and Takehisa Yairi · 2014
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Graph based anomaly detection and description: a survey
Leman Akoglu, Hanghang Tong, and Danai Koutra · 2015
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Collective opinion spam detection: Bridging review networks and metadata
Shebuti Rayana and Leman Akoglu · 2015
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Link prediction in social networks: The state-of-the-art
Peng Wang, BaoWen Xu, YuRong Wu, and XiaoYu Zhou · 2015
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
Cited alongside, same era.
Variational graph auto-encoders
Thomas N Kipf and Max Welling · 2016
Cited alongside, same era.
Less is more: Building selective anomaly ensembles
Shebuti Rayana and Leman Akoglu · 2016
Cited alongside, same era.
Intelligent financial fraud detection: a comprehensive review
Jarrod West and Maumita Bhattacharya · 2016
Cited alongside, same era.
Revisiting semi-supervised learning with graph embeddings
Zhilin Yang, William Cohen, and Ruslan Salakhudinov · 2016
Cited alongside, same era.
Representation learning on graphs: Methods and applications
William L Hamilton, Rex Ying, and Jure Leskovec · 2017
Cited alongside, same era.
Open graph benchmark: Datasets for machine learning on graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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Inductive representation learning on temporal graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, and Kannan Achan · 2020
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Few-shot network anomaly detection via cross-network meta-learning
Kaize Ding, Qinghai Zhou, Hanghang Tong, and Huan Liu · 2021
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Ogb-lsc: A large-scale challenge for machine learning on graphs
Weihua Hu, Matthias Fey, Hongyu Ren, Maho Nakata, Yuxiao Dong, and Jure Leskovec · 2021
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Large scale learning on non-homophilous graphs: New benchmarks and strong simple methods
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
Cited alongside, same era.
Radar: Residual analysis for anomaly detection in attributed networks
Jundong Li, Harsh Dani, Xia Hu, and Huan Liu · 2017
Cited alongside, same era.
Modeling relational data with graph convolutional network
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling · 2018
Cited alongside, same era.
An end-to-end deep learning architecture for graph classification
Muhan Zhang, Zhicheng Cui, Marion Neumann, and Yixin Chen · 2018
Cited alongside, same era.
Deep anomaly detection on attributed networks
Kaize Ding, Jundong Li, Rohit Bhanushali, and Huan Liu · 2019
Cited alongside, same era.
Deep anomaly detection with deviation networks
Guansong Pang, Chunhua Shen, and Anton van den Hengel · 2019
Cited alongside, same era.
Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, and Ser Nam Lim · 2021
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Pick and choose: A gnn-based imbalanced learning approach for fraud detection
Yang Liu, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang, and Qing He · 2021
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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, and Leman Akoglu · 2021
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How effective are graph neural networks in fraud detection for network data?
Ronald DR Pereira and Fabrício Murai · 2021
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One-class graph neural networks for anomaly detection in attributed networks
Xuhong Wang, Baihong Jin, Ying Du, Ping Cui, Yingshui Tan, and Yupu Yang · 2021
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Higher-order structure based anomaly detection on attributed networks
Xu Yuan, Na Zhou, Shuo Yu, Huafei Huang, Zhikui Chen, and Feng Xia · 2021
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Fraudre: Fraud detection dual-resistant to graph inconsistency and imbalance
Ge Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, and Quan Z Sheng · 2021
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Can abnormality be detected by graph neural networks?
Ziwei Chai, Siqi You, Yang Yang, Shiliang Pu, Jiarong Xu, Haoyang Cai, and Weihao Jiang · 2022
Closest in time.
Auc-oriented graph neural network for fraud detection
Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Hao Yang, and Qing He · 2022
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Pygod: A python library for graph outlier detection
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, et al · 2022
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Comga: Community-aware attributed graph anomaly detection
Xuexiong Luo, Jia Wu, Amin Beheshti, Jian Yang, Xiankun Zhang, Yuan Wang, and Shan Xue · 2022
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