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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:

Benchmark and Survey of Automated Machine Learning Frameworks
Marc-André Zöller, Marco F. Huber
Journal of Artificial Intelligence Research (2021) Vol. 70, pp. 409-472
Open Access | Times Cited: 307

Showing 1-25 of 307 citing articles:

On hyperparameter optimization of machine learning algorithms: Theory and practice
Li Yang, Abdallah Shami
Neurocomputing (2020) Vol. 415, pp. 295-316
Open Access | Times Cited: 2085
AutoML: A survey of the state-of-the-art
Xin He, Kaiyong Zhao, Xiaowen Chu
Knowledge-Based Systems (2020) Vol. 212, pp. 106622-106622
Open Access | Times Cited: 1277
Machine learning in agriculture domain: A state-of-art survey
Vishal Meshram, Kailas Patil, Vidula Meshram, et al.
Artificial Intelligence in the Life Sciences (2021) Vol. 1, pp. 100010-100010
Open Access | Times Cited: 241
Analysis and prediction of water quality using deep learning and auto deep learning techniques
D. Venkata Vara Prasad, Lokeswari Venkataramana, P. Senthil Kumar, et al.
The Science of The Total Environment (2022) Vol. 821, pp. 153311-153311
Closed Access | Times Cited: 87
AutoML: state of the art with a focus on anomaly detection, challenges, and research directions
Maroua Bahri, Flavia Salutari, Andrian Putina, et al.
International Journal of Data Science and Analytics (2022) Vol. 14, Iss. 2, pp. 113-126
Open Access | Times Cited: 78
Near real-time wind speed forecast model with bidirectional LSTM networks
Lionel Joseph, Ravinesh C. Deo, Ramendra Prasad, et al.
Renewable Energy (2023) Vol. 204, pp. 39-58
Closed Access | Times Cited: 78
Automated data processing and feature engineering for deep learning and big data applications: A survey
Alhassan Mumuni, Fuseini Mumuni
Journal of Information and Intelligence (2024)
Open Access | Times Cited: 32
Automated Machine Learning
Florian Karl, Janek Thomas, Jannes Elstner, et al.
(2024), pp. 3-25
Closed Access | Times Cited: 29
Automated machine learning: past, present and future
Mitra Baratchi, Can Wang, Steffen Limmer, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 15
Data-centric Artificial Intelligence: A Survey
Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, et al.
ACM Computing Surveys (2025)
Open Access | Times Cited: 4
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods
Alhassan Mumuni, Fuseini Mumuni
Knowledge and Information Systems (2025)
Closed Access | Times Cited: 1
A Comparison of AutoML Tools for Machine Learning, Deep Learning and XGBoost
Luís Ferreira, André Pilastri, Carlos Martins, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2021), pp. 1-8
Open Access | Times Cited: 89
Automated Machine Learning for High-Throughput Image-Based Plant Phenotyping
Joshua C.O. Koh, G. Spangenberg, Surya Kant
Remote Sensing (2021) Vol. 13, Iss. 5, pp. 858-858
Open Access | Times Cited: 77
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.
Nick Erickson, Jonas Mueller, Alexander Shirkov, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 75
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
Marcel Wever, Alexander Tornede, Felix Mohr, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) Vol. 43, Iss. 9, pp. 3037-3054
Open Access | Times Cited: 62
A Comparative study of Hyper-Parameter Optimization Tools
Shashank Shekhar, Adesh Bansode, Asif Salim
2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) (2021), pp. 1-6
Open Access | Times Cited: 61
Meta-features for meta-learning
Adriano Rívolli, Luís P. F. Garcia, Carlos Soares, et al.
Knowledge-Based Systems (2022) Vol. 240, pp. 108101-108101
Open Access | Times Cited: 60
An Effective Heart Disease Detection and Severity Level Classification Model Using Machine Learning and Hyperparameter Optimization Methods
Abdallah Abdellatif, Hamdan Abdellatef, Jeevan Kanesan, et al.
IEEE Access (2022) Vol. 10, pp. 79974-79985
Open Access | Times Cited: 59
Automated evolutionary approach for the design of composite machine learning pipelines
Nikolay O. Nikitin, Pavel Vychuzhanin, Mikhail Sarafanov, et al.
Future Generation Computer Systems (2021) Vol. 127, pp. 109-125
Open Access | Times Cited: 58
A survey on neural networks for (cyber-) security and (cyber-) security of neural networks
Marek Pawlicki, Rafał Kozik, Michał Choraś
Neurocomputing (2022) Vol. 500, pp. 1075-1087
Open Access | Times Cited: 48
IoT data analytics in dynamic environments: From an automated machine learning perspective
Li Yang, Abdallah Shami
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105366-105366
Open Access | Times Cited: 48
Review of automated time series forecasting pipelines
Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2022) Vol. 12, Iss. 6
Open Access | Times Cited: 44
Predicting biomass composition and operating conditions in fluidized bed biomass gasifiers: An automated machine learning approach combined with cooperative game theory
Jun Young Kim, Ui Hyeon Shin, Kwangsu Kim
Energy (2023) Vol. 280, pp. 128138-128138
Closed Access | Times Cited: 26
Optimizing Machine Learning Algorithms for Landslide Susceptibility Mapping along the Karakoram Highway, Gilgit Baltistan, Pakistan: A Comparative Study of Baseline, Bayesian, and Metaheuristic Hyperparameter Optimization Techniques
Farkhanda Abbas, Feng Zhang, Muhammad Ismail, et al.
Sensors (2023) Vol. 23, Iss. 15, pp. 6843-6843
Open Access | Times Cited: 26
Towards Green Automated Machine Learning: Status Quo and Future Directions
Tanja Tornede, Alexander Tornede, Jonas Hanselle, et al.
Journal of Artificial Intelligence Research (2023) Vol. 77, pp. 427-457
Open Access | Times Cited: 23
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