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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:

Automated Machine Learning
Frank Hutter, Lars Kotthoff, Joaquin Vanschoren
˜The œSpringer series on challenges in machine learning (2019)
Closed Access | Times Cited: 1024

Showing 26-50 of 1024 citing articles:

Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning
Andrea Skolik, Sofiène Jerbi, Vedran Dunjko
Quantum (2022) Vol. 6, pp. 720-720
Open Access | Times Cited: 110
Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis
Marcus H. Reis, Filipp Gusev, Nicholas G. Taylor, et al.
Journal of the American Chemical Society (2021) Vol. 143, Iss. 42, pp. 17677-17689
Closed Access | Times Cited: 107
Automated Machine Learning for Healthcare and Clinical Notes Analysis
Akram Mustafa, Mostafa Rahimi Azghadi
Computers (2021) Vol. 10, Iss. 2, pp. 24-24
Open Access | Times Cited: 101
Machine learning (ML)-centric resource management in cloud computing: A review and future directions
Tahseen Khan, Wenhong Tian, Guangyao Zhou, et al.
Journal of Network and Computer Applications (2022) Vol. 204, pp. 103405-103405
Open Access | Times Cited: 95
Predicting student's dropout in university classes using two-layer ensemble machine learning approach: A novel stacked generalization
Jovial Niyogisubizo, Lyuchao Liao, Eric Nziyumva, et al.
Computers and Education Artificial Intelligence (2022) Vol. 3, pp. 100066-100066
Open Access | Times Cited: 88
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
State of health estimation of lithium-ion batteries with a temporal convolutional neural network using partial load profiles
Steffen Bockrath, Vincent Lorentz, Marco Pruckner
Applied Energy (2022) Vol. 329, pp. 120307-120307
Open Access | Times Cited: 76
Data quantity governance for machine learning in materials science
Yue Liu, Zhengwei Yang, Xinxin Zou, et al.
National Science Review (2023) Vol. 10, Iss. 7
Open Access | Times Cited: 73
A review of machine learning methods applied to structural dynamics and vibroacoustic
Barbara Zaparoli Cunha, Christophe Droz, Abdelmalek Zine, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110535-110535
Open Access | Times Cited: 72
Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models
Elissaios Sarmas, Evangelos Spiliotis, Efstathios Stamatopoulos, et al.
Renewable Energy (2023) Vol. 216, pp. 118997-118997
Open Access | Times Cited: 62
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao Hai, Sani I. Abba, Ahmed M. Al‐Areeq, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107559-107559
Closed Access | Times Cited: 57
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
Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer
Daniel E. Spratt, Siyi Tang, Yilun Sun, et al.
NEJM Evidence (2023) Vol. 2, Iss. 8
Open Access | Times Cited: 49
A Survey on Optimization Techniques for Edge Artificial Intelligence (AI)
Chellammal Surianarayanan, John Jeyasekaran Lawrence, Pethuru Raj Chelliah, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1279-1279
Open Access | Times Cited: 41
A survey on model-based reinforcement learning
Fan-Ming Luo, Tian Xu, Hang Lai, et al.
Science China Information Sciences (2024) Vol. 67, Iss. 2
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
Identifying Human Factors in Aviation Accidents with Natural Language Processing and Machine Learning Models
Flávio L. Lázaro, Tomás Madeira, Rui Melício, et al.
Aerospace (2025) Vol. 12, Iss. 2, pp. 106-106
Open Access | Times Cited: 1
Automated Machine Learning of Interfacial Interaction Descriptors and Energies in Metal-Catalyzed N2 and CO2 Reduction Reactions
Jiawei Chen, Yuming Gu, Qin Zhu, et al.
Langmuir (2025) Vol. 41, Iss. 5, pp. 3490-3502
Closed Access | Times Cited: 1
Deep-Reinforcement-Learning-Based Autonomous UAV Navigation With Sparse Rewards
Chao Wang, Jian Wang, Jingjing Wang, et al.
IEEE Internet of Things Journal (2020) Vol. 7, Iss. 7, pp. 6180-6190
Closed Access | Times Cited: 134
Analysis of the Human Protein Atlas Image Classification competition
Wei Ouyang, Casper F. Winsnes, Martin Hjelmare, et al.
Nature Methods (2019) Vol. 16, Iss. 12, pp. 1254-1261
Open Access | Times Cited: 108
A data-driven interval forecasting model for building energy prediction using attention-based LSTM and fuzzy information granulation
Yue Li, Zheming Tong, Shuiguang Tong, et al.
Sustainable Cities and Society (2021) Vol. 76, pp. 103481-103481
Closed Access | Times Cited: 99
A New Reinforcement Learning Based Learning Rate Scheduler for Convolutional Neural Network in Fault Classification
Long Wen, Xinyu Li, Liang Gao
IEEE Transactions on Industrial Electronics (2020) Vol. 68, Iss. 12, pp. 12890-12900
Closed Access | Times Cited: 98
TBM performance prediction with Bayesian optimization and automated machine learning
Qianli Zhang, Weifei Hu, Zhenyu Liu, et al.
Tunnelling and Underground Space Technology (2020) Vol. 103, pp. 103493-103493
Closed Access | Times Cited: 94
Implementing AutoML in Educational Data Mining for Prediction Tasks
Maria Tsiakmaki, Georgios Kostopoulos, Sotiris Kotsiantis, et al.
Applied Sciences (2019) Vol. 10, Iss. 1, pp. 90-90
Open Access | Times Cited: 89

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