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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:

Auto-sklearn: Efficient and Robust Automated Machine Learning
Matthias Feurer, Aaron Klein, Katharina Eggensperger, et al.
˜The œSpringer series on challenges in machine learning (2019), pp. 113-134
Open Access | Times Cited: 333

Showing 1-25 of 333 citing articles:

Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence
Sebastian Raschka, Joshua Patterson, Corey Nolet
Information (2020) Vol. 11, Iss. 4, pp. 193-193
Open Access | Times Cited: 451
Automatic tuning of hyperparameters using Bayesian optimization
A. Helen Victoria, G. Maragatham
Evolving Systems (2020) Vol. 12, Iss. 1, pp. 217-223
Closed Access | Times Cited: 350
MedMNIST v2 - A large-scale lightweight benchmark for 2D and 3D biomedical image classification
Jiancheng Yang, Rui Shi, Donglai Wei, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 328
capAI - A Procedure for Conducting Conformity Assessment of AI Systems in Line with the EU Artificial Intelligence Act
Luciano Floridi, Matthias Holweg, Mariarosaria Taddeo, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 112
Review of ML and AutoML Solutions to Forecast Time-Series Data
Ahmad Alsharef, Karan Aggarwal, Sonia Sonia, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 7, pp. 5297-5311
Open Access | Times Cited: 90
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
An Explainable AI-Based Intrusion Detection System for DNS Over HTTPS (DoH) Attacks
Tahmina Zebin, Shahadate Rezvy, Yuan Luo
IEEE Transactions on Information Forensics and Security (2022) Vol. 17, pp. 2339-2349
Open Access | Times Cited: 77
Bayesian Optimization
Hao Wang, Kaifeng Yang
Natural computing series (2023), pp. 271-297
Closed Access | Times Cited: 61
An improved hyperparameter optimization framework for AutoML systems using evolutionary algorithms
Amala Mary Vincent, P. Jidesh
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 56
Lightweight Deep Learning for Resource-Constrained Environments: A Survey
Hou-I Liu, Marco Antonio Gutiérrez Galindo, Hongxia Xie, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 10, pp. 1-42
Open Access | Times Cited: 18
Automated Machine Learning: The New Wave of Machine Learning
Karansingh Chauhan, Shreena Jani, Dhrumin Thakkar, et al.
(2020), pp. 205-212
Closed Access | Times Cited: 85
A Generic Deep Learning Based Cough Analysis System From Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels
Javier Andreu-Pérez, Humberto Pérez-Espinosa, Eva Timonet‐Andreu, et al.
IEEE Transactions on Services Computing (2021) Vol. 15, Iss. 3, pp. 1220-1232
Open Access | Times Cited: 80
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
Automated Machine Learning—A Brief Review at the End of the Early Years
Hugo Jair Escalante
Natural computing series (2021), pp. 11-28
Closed Access | Times Cited: 73
Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and outlook
Omar M. Abdeldayem, Areeg M. Dabbish, Mahmoud M. Habashy, et al.
The Science of The Total Environment (2021) Vol. 803, pp. 149834-149834
Open Access | Times Cited: 67
Ensemble learning models with a Bayesian optimization algorithm for mineral prospectivity mapping
Jiangning Yin, Nan Li
Ore Geology Reviews (2022) Vol. 145, pp. 104916-104916
Open Access | Times Cited: 65
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
Automated Machine Learning on Graphs: A Survey
Ziwei Zhang, Xin Wang, Wenwu Zhu
(2021)
Open Access | Times Cited: 56
Simple Deterministic Selection-Based Genetic Algorithm for Hyperparameter Tuning of Machine Learning Models
Ismail Damilola Raji, Habeeb Bello-Salau, Ime J. Umoh, et al.
Applied Sciences (2022) Vol. 12, Iss. 3, pp. 1186-1186
Open Access | Times Cited: 45
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling
Filipp Gusev, Evgeny Gutkin, Maria Kurnikova, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 2, pp. 583-594
Open Access | Times Cited: 35
Bibliometric methods in traffic flow prediction based on artificial intelligence
Yong Chen, Wanru Wang, Xiqun Chen
Expert Systems with Applications (2023) Vol. 228, pp. 120421-120421
Closed Access | Times Cited: 26
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS
Gary Tom, Riley J. Hickman, Aniket Zinzuwadia, et al.
Digital Discovery (2023) Vol. 2, Iss. 3, pp. 759-774
Open Access | Times Cited: 25
SR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning Method
Hengzhe Zhang, Aimin Zhou, Qi Chen, et al.
IEEE Transactions on Evolutionary Computation (2023) Vol. 28, Iss. 5, pp. 1484-1498
Closed Access | Times Cited: 22
Global optimization via inverse distance weighting and radial basis functions
Alberto Bemporad
Computational Optimization and Applications (2020) Vol. 77, Iss. 2, pp. 571-595
Open Access | Times Cited: 56
Identification and Application of Machine Learning Algorithms for Transformer Dissolved Gas Analysis
U. Mohan Rao, I. Fofana, Kandala N. V. P. S. Rajesh, et al.
IEEE Transactions on Dielectrics and Electrical Insulation (2021) Vol. 28, Iss. 5, pp. 1828-1835
Closed Access | Times Cited: 54
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