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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.

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Denis Baylor, Eric Breck, Heng-Tze Cheng, et al.
(2017)
Open Access | Times Cited: 286

Showing 1-25 of 286 citing articles:

Software Engineering for Machine Learning: A Case Study
Saleema Amershi, Andrew Begel, Christian Bird, et al.
(2019), pp. 291-300
Closed Access | Times Cited: 794
A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective
Yuji Roh, Geon Heo, Steven Euijong Whang
IEEE Transactions on Knowledge and Data Engineering (2019) Vol. 33, Iss. 4, pp. 1328-1347
Open Access | Times Cited: 726
Machine Learning Testing: Survey, Landscapes and Horizons
Jie M. Zhang, Mark Harman, Lei Ma, et al.
IEEE Transactions on Software Engineering (2020) Vol. 48, Iss. 1, pp. 1-36
Open Access | Times Cited: 698
Deep Neural Networks and Tabular Data: A Survey
Vadim Borisov, Tobias Leemann, Kathrin Seßler, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 6, pp. 7499-7519
Open Access | Times Cited: 425
The What-If Tool: Interactive Probing of Machine Learning Models
James Wexler, Mahima Pushkarna, Tolga Bolukbasi, et al.
IEEE Transactions on Visualization and Computer Graphics (2019), pp. 1-1
Open Access | Times Cited: 417
Advances, challenges and opportunities in creating data for trustworthy AI
Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 8, pp. 669-677
Closed Access | Times Cited: 270
Recommending what video to watch next
Zhe Zhao, Lichan Hong, Wei Li, et al.
(2019)
Closed Access | Times Cited: 261
Cyber Security Threats Detection in Internet of Things Using Deep Learning Approach
Farhan Ullah, Hamad Naeem, Sohail Jabbar, et al.
IEEE Access (2019) Vol. 7, pp. 124379-124389
Open Access | Times Cited: 200
Towards Accountability for Machine Learning Datasets
Ben Hutchinson, Andrew Smart, Alex Hanna, et al.
(2021), pp. 560-575
Open Access | Times Cited: 200
The ML test score: A rubric for ML production readiness and technical debt reduction
Eric Breck, Shanqing Cai, Eric Nielsen, et al.
2021 IEEE International Conference on Big Data (Big Data) (2017), pp. 1123-1132
Closed Access | Times Cited: 180
Data Lifecycle Challenges in Production Machine Learning
Neoklis Polyzotis, Sudip Roy, Steven Euijong Whang, et al.
ACM SIGMOD Record (2018) Vol. 47, Iss. 2, pp. 17-28
Closed Access | Times Cited: 167
Software Engineering for AI-Based Systems: A Survey
Silverio Martínez‐Fernández, Justus Bogner, Xavier Franch, et al.
ACM Transactions on Software Engineering and Methodology (2022) Vol. 31, Iss. 2, pp. 1-59
Open Access | Times Cited: 167
Automating large-scale data quality verification
Sebastian Schelter, Dustin Lange, Philipp Schmidt, et al.
Proceedings of the VLDB Endowment (2018) Vol. 11, Iss. 12, pp. 1781-1794
Closed Access | Times Cited: 166
How does Machine Learning Change Software Development Practices?
Zhiyuan Wan, Xin Xia, David Lo, et al.
IEEE Transactions on Software Engineering (2019), pp. 1-1
Open Access | Times Cited: 154
Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology
Stefan Studer, Thanh Binh Bui, Christian Drescher, et al.
Machine Learning and Knowledge Extraction (2021) Vol. 3, Iss. 2, pp. 392-413
Open Access | Times Cited: 151
Large-scale machine learning systems in real-world industrial settings: A review of challenges and solutions
Lucy Ellen Lwakatare, Aiswarya Raj, Ivica Crnković, et al.
Information and Software Technology (2020) Vol. 127, pp. 106368-106368
Closed Access | Times Cited: 138
Managing Bias in AI
Drew Roselli, Jeanna Matthews, Nisha Talagala
(2019), pp. 539-544
Closed Access | Times Cited: 131
Big Data Systems Meet Machine Learning Challenges: Towards Big Data Science as a Service
Radwa Elshawi, Sherif Sakr, Domenico Talia, et al.
Big Data Research (2018) Vol. 14, pp. 1-11
Open Access | Times Cited: 127
Snorkel DryBell
Stephen H. Bach, Daniel Rodriguez Gutierrez, Yintao Liu, et al.
Proceedings of the 2022 International Conference on Management of Data (2019), pp. 362-375
Open Access | Times Cited: 93
Data collection and quality challenges for deep learning
Steven Euijong Whang, Jae-Gil Lee
Proceedings of the VLDB Endowment (2020) Vol. 13, Iss. 12, pp. 3429-3432
Closed Access | Times Cited: 90
Elastic Machine Learning Algorithms in Amazon SageMaker
Edo Liberty, Zohar Karnin, Bing Xiang, et al.
(2020), pp. 731-737
Closed Access | Times Cited: 88
Adoption and Effects of Software Engineering Best Practices in Machine Learning
Alex Serban, Koen van der Blom, Holger H. Hoos, et al.
(2020), pp. 1-12
Open Access | Times Cited: 88
Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence
David W. Bates, Andrew D. Auerbach, Peter Schulam, et al.
Annals of Internal Medicine (2020) Vol. 172, Iss. 11_Supplement, pp. S137-S144
Closed Access | Times Cited: 83
ModelOps: Cloud-Based Lifecycle Management for Reliable and Trusted AI
Waldemar Hummer, Vinod Muthusamy, Thomas Rausch, et al.
(2019), pp. 113-120
Closed Access | Times Cited: 82
Augmented Normalized Difference Water Index for improved surface water monitoring
Arash Modaresi Rad, Jason Kreitler, Mojtaba Sadegh
Environmental Modelling & Software (2021) Vol. 140, pp. 105030-105030
Open Access | Times Cited: 80
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