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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:

Interpretable Machine Learning for Discovery: Statistical Challenges and Opportunities
Genevera I. Allen, Luqin Gan, Lili Zheng
Annual Review of Statistics and Its Application (2023) Vol. 11, Iss. 1, pp. 97-121
Open Access | Times Cited: 24

Showing 24 citing articles:

JARVIS-Leaderboard: a large scale benchmark of materials design methods
Kamal Choudhary, Daniel Wines, Kangming Li, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 14
Novel high-content and open-source image analysis tools for profiling mitochondrial morphology in neurological cell models
Marcus Y. Chin, David A. Joy, Madhuja Samaddar, et al.
SLAS DISCOVERY (2025), pp. 100208-100208
Open Access | Times Cited: 1
Computational frameworks integrating deep learning and statistical models in mining multimodal omics data
Leann Lac, Carson K. Leung, Pingzhao Hu
Journal of Biomedical Informatics (2024) Vol. 152, pp. 104629-104629
Open Access | Times Cited: 7
A review of unsupervised learning in astronomy
S. Fotopoulou
Astronomy and Computing (2024) Vol. 48, pp. 100851-100851
Open Access | Times Cited: 6
“Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”
Nathaniel K. Newlands, Vyacheslav Lyubchich
Environmetrics (2025) Vol. 36, Iss. 2
Open Access
Advancements in Nanocomposites: An In-depth Exploration of Microstructural, Electrical, and Mechanical Dynamics
Fernando Gomes de Souza, Shekhar Bhansali, Kaushik Pal, et al.
(2024)
Open Access | Times Cited: 4
Decoding Nanomaterial‐Biosystem Interactions through Machine Learning
Sagar Dhoble, Tzu‐Hsien Wu, Kenry Kenry
Angewandte Chemie International Edition (2024) Vol. 63, Iss. 16
Closed Access | Times Cited: 4
A 30-Year Review on Nanocomposites: Comprehensive Bibliometric Insights into Microstructural, Electrical, and Mechanical Properties Assisted by Artificial Intelligence
Fernando Gomes de Souza, Shekhar Bhansali, Kaushik Pal, et al.
Materials (2024) Vol. 17, Iss. 5, pp. 1088-1088
Open Access | Times Cited: 4
Using a multiphysics coupling-oriented flood modelling approach to assess urban flooding under various regulation scenarios combined with rainstorms and tidal effects
Yongshuai Liang, Weihong Liao, Zhao Zhang, et al.
Journal of Hydrology (2024), pp. 132189-132189
Closed Access | Times Cited: 4
Improving predictive maintenance: Evaluating the impact of preprocessing and model complexity on the effectiveness of eXplainable Artificial Intelligence methods
M. Ndao, Genane Youness, Ndèye Niang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110144-110144
Open Access
Advanced computational techniques: Bridging metaheuristic optimization and deep learning for material design through image enhancement
Jagrati Talreja, Divya Chauhan
Elsevier eBooks (2025), pp. 197-228
Closed Access
Interpretable deep learning in single-cell omics
Manoj M Wagle, Siqu Long, Carissa Chen, et al.
Bioinformatics (2024) Vol. 40, Iss. 6
Open Access | Times Cited: 3
Decoding Nanomaterial‐Biosystem Interactions through Machine Learning
Sagar Dhoble, Tzu‐Hsien Wu, Kenry Kenry
Angewandte Chemie (2024) Vol. 136, Iss. 16
Closed Access | Times Cited: 1
Customer Acquisition Via Explainable Deep Reinforcement Learning
Yicheng Song, Wenbo Wang, Song Yao
SSRN Electronic Journal (2024)
Closed Access | Times Cited: 1
Large Scale Benchmark of Materials Design Methods
Kamal Choudhary, Daniel Wines, Kangming Li, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
Hug-Iml: Interpretable Machine Learning for Decision Support Using High Utility Gain Patterns
Srikumar Krishnamoorthy
(2024)
Closed Access
Customer Acquisition via Explainable Deep Reinforcement Learning
Yicheng Song, Wenbo Wang, Song Yao
Information Systems Research (2024)
Closed Access
Novel high-content and open-source image analysis tools for profiling mitochondrial morphology in neurological cell models
Marcus Y. Chin, David A. Joy, Madhuja Samaddar, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Space-Time Causal Discovery in Climate Science: A Local Stencil Learning Approach
J. Jake Nichol, J. Jake Nichol, Michael Weylandt, et al.
Authorea (Authorea) (2024)
Open Access
Interpretable classifier models for decision support using high utility gain patterns
Srikumar Krishnamoorthy
IEEE Access (2024) Vol. 12, pp. 126088-126107
Open Access
Viewing the process of generating counterfactuals as a source of knowledge: a new approach for explaining classifiers
Vincent Lemaire, Nathan Le Boudec, Victor Guyomard, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. v2, pp. 1-8
Closed Access
回归分析中的两类假设检验问题
Xinyu Zhang, Shi Yanmei, Xu Guo
Scientia Sinica Mathematica (2024)
Closed Access
Graph-Based Feature Engineering for Enhanced Machine Learning in Rolling Element Bearing Fault Diagnosis
Seyed Mohammad Hosseini, Abolfazl Dibaji, Sadegh Sulaimany
Engineering Research Express (2024) Vol. 6, Iss. 4, pp. 045234-045234
Closed Access
Hidden Knowledge Recovery from GAN-generated Single-cell RNA-seq Data
Najeebullah Shah, Fanhong Li, Xuegong Zhang
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
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