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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

NetWalk
Wenchao Yu, Wei Cheng, Charų C. Aggarwal, et al.
(2018), pp. 2672-2681
Open Access | Times Cited: 289

Showing 1-25 of 289 citing articles:

Deep Learning for Anomaly Detection
Guansong Pang, Chunhua Shen, Longbing Cao, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 2, pp. 1-38
Open Access | Times Cited: 1535
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
Dan Li, Dacheng Chen, Baihong Jin, et al.
Lecture notes in computer science (2019), pp. 703-716
Closed Access | Times Cited: 775
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning
Xiaoxiao Ma, Jia Wu, Shan Xue, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 12, pp. 12012-12038
Open Access | Times Cited: 400
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
Yixin Liu, Zhao Li, Shirui Pan, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 6, pp. 2378-2392
Open Access | Times Cited: 218
FdGars: Fraudster Detection via Graph Convolutional Networks in Online App Review System
Jianyu Wang, Rui Wen, Chunming Wu, et al.
(2019)
Closed Access | Times Cited: 173
Dynamic network embedding survey
Guotong Xue, Ming Zhong, Jianxin Li, et al.
Neurocomputing (2021) Vol. 472, pp. 212-223
Open Access | Times Cited: 172
Graph Neural Networks for Anomaly Detection in Industrial Internet of Things
Yulei Wu, Hong‐Ning Dai, Haina Tang
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 12, pp. 9214-9231
Open Access | Times Cited: 166
E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction
Jinyin Chen, Jian Zhang, Xuanheng Xu, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2019) Vol. 51, Iss. 6, pp. 3699-3712
Open Access | Times Cited: 163
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
Dan Li, Dacheng Chen, Baihong Jin, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 145
Graph Neural Network: A Comprehensive Review on Non-Euclidean Space
Nurul A. Asif, Yeahia Sarker, Ripon K. Chakrabortty, et al.
IEEE Access (2021) Vol. 9, pp. 60588-60606
Open Access | Times Cited: 133
ROLAND: Graph Learning Framework for Dynamic Graphs
Jiaxuan You, Tianyu Du, Jure Leskovec
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 2358-2366
Open Access | Times Cited: 87
Temporal Network Embedding with Micro- and Macro-dynamics
Yuanfu Lu, Xiao Wang, Chuan Shi, et al.
(2019), pp. 469-478
Open Access | Times Cited: 115
Feature Encoding With Autoencoders for Weakly Supervised Anomaly Detection
Yingjie Zhou, Xucheng Song, Yanru Zhang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 6, pp. 2454-2465
Open Access | Times Cited: 99
A Survey on Embedding Dynamic Graphs
Claudio D. T. Barros, Matheus R. F. Mendonça, Alex Borges Vieira, et al.
ACM Computing Surveys (2021) Vol. 55, Iss. 1, pp. 1-37
Open Access | Times Cited: 96
Deep Representation Learning for Social Network Analysis
Qiaoyu Tan, Ninghao Liu, Xia Hu
Frontiers in Big Data (2019) Vol. 2
Open Access | Times Cited: 85
A graph neural network method for distributed anomaly detection in IoT
Aikaterini Protogerou, Stavros Papadopoulos, Anastasios Drosou, et al.
Evolving Systems (2020) Vol. 12, Iss. 1, pp. 19-36
Open Access | Times Cited: 83
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
Lei Cai, Zhengzhang Chen, Chen Luo, et al.
(2021)
Open Access | Times Cited: 77
SpecAE
Yuening Li, Xiao Huang, Jundong Li, et al.
(2019)
Open Access | Times Cited: 76
Temporal Network Embedding for Link Prediction via VAE Joint Attention Mechanism
Pengfei Jiao, Xuan Guo, Xin Jing, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 12, pp. 7400-7413
Closed Access | Times Cited: 64
Anomaly Detection in Dynamic Graphs via Transformer
Yixin Liu, Shirui Pan, Yu Guang Wang, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 12, pp. 12081-12094
Open Access | Times Cited: 60
A survey of outlier detection in high dimensional data streams
Imen Souiden, Mohamed Nazih Omri, Zaki Brahmi
Computer Science Review (2022) Vol. 44, pp. 100463-100463
Closed Access | Times Cited: 50
TimeAutoAD: Autonomous Anomaly Detection With Self-Supervised Contrastive Loss for Multivariate Time Series
Yang Jiao, Kai Yang, Dongjing Song, et al.
IEEE Transactions on Network Science and Engineering (2022) Vol. 9, Iss. 3, pp. 1604-1619
Closed Access | Times Cited: 39
RegraphGAN: A graph generative adversarial network model for dynamic network anomaly detection
Dezhi Guo, Zhaowei Liu, Ranran Li
Neural Networks (2023) Vol. 166, pp. 273-285
Closed Access | Times Cited: 24
A Survey of Graph-Based Deep Learning for Anomaly Detection in Distributed Systems
Armin Danesh Pazho, Ghazal Alinezhad Noghre, Arnab A Purkayastha, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 1, pp. 1-20
Open Access | Times Cited: 22
Temporal Link Prediction: A Unified Framework, Taxonomy, and Review
Meng Qin, Dit‐Yan Yeung
ACM Computing Surveys (2023) Vol. 56, Iss. 4, pp. 1-40
Open Access | Times Cited: 22
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