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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:

Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data
Georg Steinbuß, Klemens Böhm
ACM Transactions on Knowledge Discovery from Data (2021) Vol. 15, Iss. 4, pp. 1-20
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Anomaly detection in streaming data: A comparison and evaluation study
Félix Iglesias, Alexander Härtl, Tanja Zseby, et al.
Expert Systems with Applications (2023) Vol. 233, pp. 120994-120994
Open Access | Times Cited: 13
Synthetic Data Generation
Edlira Martiri
Advances in business information systems and analytics book series (2024), pp. 118-138
Closed Access | Times Cited: 5
Generation of Synthetic Image Anomalies for Analysis
David Breuss, Karel Rusý, Maximilian Götzinger, et al.
Communications in computer and information science (2025), pp. 13-27
Closed Access
Ensuring real-time data integrity in Smart Building Applications: A systematic end-to-end comprehensive pipeline evaluated in numerous real-life cases
Aliki Stefanopoulou, Iakovos Michailidis, Georgios D. Karatzinis, et al.
Energy and Buildings (2025), pp. 115586-115586
Closed Access
Sensor Fusion Enhances Anomaly Detection in a Flood Forecasting System
Andrew Ma, Abhir Karande, Natalie Dahlquist, et al.
Journal of Sensor and Actuator Networks (2025) Vol. 14, Iss. 2, pp. 34-34
Open Access
Unsupervised outlier detection using neural network-based mixtures of probabilistic principal component analyzers for building chiller fault diagnosis
Viet Tra, Manar Amayri, Nizar Bouguila
Building and Environment (2022) Vol. 225, pp. 109620-109620
Closed Access | Times Cited: 14
Procedure code overutilization detection from healthcare claims using unsupervised deep learning methods
Michael Suesserman, Samantha Gorny, Daniel Lasaga, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 8
Anomaly Detection with Score Distribution Discrimination
Minqi Jiang, Songqiao Han, Hailiang Huang
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 984-996
Open Access | Times Cited: 5
Outlier detection based on extreme value theory and applications
Shrijita Bhattacharya, Francois Kamper, Jan Beirlant
Scandinavian Journal of Statistics (2023) Vol. 50, Iss. 3, pp. 1466-1502
Open Access | Times Cited: 4
Outlier Detection in Auditing: Integrating Unsupervised Learning within a Multilevel Framework for General Ledger Analysis
Danyang Wei, Soohyun Cho, Miklos A. Vasarhelyi, et al.
Journal of Information Systems (2024) Vol. 38, Iss. 2, pp. 123-142
Open Access | Times Cited: 1
Adjacent Image Augmentation and Its Framework for Self-Supervised Learning in Anomaly Detection
Gi Seung Kwon, Yong Suk Choi
Sensors (2024) Vol. 24, Iss. 17, pp. 5616-5616
Open Access | Times Cited: 1
Integrating granular computing with density estimation for anomaly detection in high-dimensional heterogeneous data
Baiyang Chen, Zhong Yuan, Dezhong Peng, et al.
Information Sciences (2024), pp. 121566-121566
Closed Access | Times Cited: 1
Toward Unsupervised Outlier Model Selection
Yue Zhao, Sean X. Zhang, Leman Akoglu
2021 IEEE International Conference on Data Mining (ICDM) (2022), pp. 773-782
Open Access | Times Cited: 4
Sparx: Distributed Outlier Detection at Scale
Sean X. Zhang, Varun Ursekar, Leman Akoglu
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 4530-4540
Open Access | Times Cited: 3
Understanding the limitations of self-supervised learning for tabular anomaly detection
T. Kimberly, T. Davies, Lewis D. Griffin
Pattern Analysis and Applications (2024) Vol. 27, Iss. 2
Open Access
What do anomaly scores actually mean? Dynamic characteristics beyond accuracy
Félix Iglesias, Henrique O. Marques, Arthur Zimek, et al.
Data Mining and Knowledge Discovery (2024) Vol. 39, Iss. 1, pp. 1-59
Open Access
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles
Kushankur Ghosh, Murilo Coelho Naldi, Jörg Sander, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 7021-7030
Closed Access
Using Autonomous Outlier Detection Methods for Thermophysical Property Data
Andrea Schnorr, Daniel Johannes Kaldi, Jens Staubach, et al.
Journal of Chemical & Engineering Data (2024) Vol. 69, Iss. 3, pp. 864-880
Closed Access
Multiple Autoencoder-Based Anomaly Detection with Fuzzy Rough Sets
Xiaofeng Tan, Can Gao, Jie Zhou, et al.
(2024)
Closed Access
A General Framework for the Assessment of Detectors of Anomalies in Time Series
Andriy Enttsel, Silvia Onofri, Alex Marchioni, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 10, pp. 12051-12061
Open Access
C-AllOut: Catching & Calling Outliers by Type.
Guilherme D. F. Silva, Leman Akoglu, Robson L. F. Cordeiro
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 1
Psychotic Disorders Relapse Prediction from Passive Signals using Anomaly Detection Methods
Salam Hamieh, Hussein Al Osman, Vincent Heiries, et al.
(2023)
Open Access
Psychotic Disorders Relapse Prediction from Passive Signals using Anomaly Detection Methods
Salam Hamieh, Hussein Al Osman, Vincent Heiries, et al.
(2023)
Open Access
Understanding the limitations of self-supervised learning for tabular anomaly detection
T. Kimberly, T. Davies, Lewis D. Griffin
arXiv (Cornell University) (2023)
Open Access
Benchmarking Anomaly Detection Algorithms using Hyperparameter Optimization
Zoltan Czako, Gheorghe Sebestyen, Anca Hângan
(2023) Vol. 23, pp. 71-78
Closed Access
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