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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:

Layer-Wise Relevance Propagation: An Overview
Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, et al.
Lecture notes in computer science (2019), pp. 193-209
Closed Access | Times Cited: 558

Showing 1-25 of 558 citing articles:

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, et al.
Lecture notes in computer science (2019)
Closed Access | Times Cited: 1082
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Guang Yang, Qinghao Ye, Jun Xia
Information Fusion (2021) Vol. 77, pp. 29-52
Open Access | Times Cited: 501
Towards Explainable Artificial Intelligence
Wojciech Samek, Klaus‐Robert Müller
Lecture notes in computer science (2019), pp. 5-22
Closed Access | Times Cited: 436
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
Explainable AI Methods - A Brief Overview
Andreas Holzinger, Anna Saranti, Christoph Molnar, et al.
Lecture notes in computer science (2022), pp. 13-38
Open Access | Times Cited: 227
Transformer-CNN: Swiss knife for QSAR modeling and interpretation
Pavel Karpov, Guillaume Godin, Igor V. Tetko
Journal of Cheminformatics (2020) Vol. 12, Iss. 1
Open Access | Times Cited: 208
Understanding deep learning in land use classification based on Sentinel-2 time series
Manuel Campos‐Taberner, Francisco Javier Garcı́a-Haro, Beatriz Martínez, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 166
Higher-Order Explanations of Graph Neural Networks via Relevant Walks
Thomas Schnake, Oliver Eberle, Jonas Lederer, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) Vol. 44, Iss. 11, pp. 7581-7596
Open Access | Times Cited: 165
A deep convolutional neural network for COVID-19 detection using chest X-rays
Pedro R. A. S. Bassi, Romis Attux
Research on Biomedical Engineering (2021) Vol. 38, Iss. 1, pp. 139-148
Open Access | Times Cited: 164
Explainability for Large Language Models: A Survey
Haiyan Zhao, Hanjie Chen, Fan Yang, et al.
ACM Transactions on Intelligent Systems and Technology (2024) Vol. 15, Iss. 2, pp. 1-38
Open Access | Times Cited: 153
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 3, pp. 247-278
Open Access | Times Cited: 152
A literature review on one-class classification and its potential applications in big data
Naeem Seliya, Azadeh Abdollah Zadeh, Taghi M. Khoshgoftaar
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 129
CTformer: convolution-free Token2Token dilated vision transformer for low-dose CT denoising
Dayang Wang, Fenglei Fan, Zhan Wu, et al.
Physics in Medicine and Biology (2023) Vol. 68, Iss. 6, pp. 065012-065012
Open Access | Times Cited: 107
CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations
Leila Arras, Ahmed Osman, Wojciech Samek
Information Fusion (2021) Vol. 81, pp. 14-40
Open Access | Times Cited: 104
Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions
Andreas Holzinger, Anna Saranti, Alessa Angerschmid, et al.
Sensors (2022) Vol. 22, Iss. 8, pp. 3043-3043
Open Access | Times Cited: 102
Explaining the differences of gait patterns between high and low-mileage runners with machine learning
Datao Xu, Wenjing Quan, Huiyu Zhou, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 98
From Clustering to Cluster Explanations via Neural Networks
Jacob Kauffmann, Malte Esders, Lukas Ruff, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 2, pp. 1926-1940
Open Access | Times Cited: 84
Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning
Minji Lee, Leandro Sanz, Alice Barra, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 84
Machine Learning-Guided Protein Engineering
Petr Kouba, Pavel Kohout, Faraneh Haddadi, et al.
ACS Catalysis (2023) Vol. 13, Iss. 21, pp. 13863-13895
Open Access | Times Cited: 83
A survey on the interpretability of deep learning in medical diagnosis
Qiaoying Teng, Zhe Liu, Yuqing Song, et al.
Multimedia Systems (2022) Vol. 28, Iss. 6, pp. 2335-2355
Open Access | Times Cited: 78
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder
IEEE Transactions on Artificial Intelligence (2023) Vol. 5, Iss. 4, pp. 1429-1442
Open Access | Times Cited: 76
Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities
Subash Neupane, Jesse Ables, William Anderson, et al.
IEEE Access (2022) Vol. 10, pp. 112392-112415
Open Access | Times Cited: 68
From attribution maps to human-understandable explanations through Concept Relevance Propagation
Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 9, pp. 1006-1019
Open Access | Times Cited: 62
Survey on Explainable AI: From Approaches, Limitations and Applications Aspects
Wenli Yang, Yu-Chen Wei, H. Wei, et al.
Human-Centric Intelligent Systems (2023) Vol. 3, Iss. 3, pp. 161-188
Open Access | Times Cited: 59
Toward Explainable Artificial Intelligence for Precision Pathology
Frederick Klauschen, Jonas Dippel, Philipp Keyl, et al.
Annual Review of Pathology Mechanisms of Disease (2023) Vol. 19, Iss. 1, pp. 541-570
Open Access | Times Cited: 48
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