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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:

Extracting knowledge from Deep Neural Networks through graph analysis
Vitor Horta, Ilaria Tiddi, Suzanne Little, et al.
Future Generation Computer Systems (2021) Vol. 120, pp. 109-118
Open Access | Times Cited: 21

Showing 21 citing articles:

Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks
Νικόλαος Γιαμαρέλος, Elias N. Zois
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101304-101304
Closed Access | Times Cited: 6
Graph data science: Applications and future
Renjith V. Ravi, Pushan Kumar Dutta, S. B. Goyal
Elsevier eBooks (2025), pp. 227-243
Closed Access
A novel fuzzy knowledge graph pairs approach in decision making
Cu Kim Long, Hai Van Pham, Trần Mạnh Tuấn, et al.
Multimedia Tools and Applications (2022) Vol. 81, Iss. 18, pp. 26505-26534
Closed Access | Times Cited: 18
Functional loops: Monitoring functional organization of deep neural networks using algebraic topology
Ben Zhang, Hongwei Lin
Neural Networks (2024) Vol. 174, pp. 106239-106239
Closed Access | Times Cited: 3
Effective graph-neural-network based models for discovering Structural Hole Spanners in large-scale and diverse networks
Diksha Goel, Hong Shen, Hui Tian, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123636-123636
Open Access | Times Cited: 3
Knowledge correlation graph-guided multi-source interaction domain adaptation network for rotating machinery fault diagnosis
Zhenghong Wu, Hongkai Jiang, Xin Wang, et al.
ISA Transactions (2023) Vol. 142, pp. 663-682
Closed Access | Times Cited: 5
A Neuro-symbolic Approach to Enhance Interpretability of Graph Neural Network through the Integration of External Knowledge
Kislay Raj
(2023), pp. 5177-5180
Open Access | Times Cited: 5
A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
Darren J. Edwards, Ciara McEnteggart, Yvonne Barnes‐Holmes
Frontiers in Psychology (2022) Vol. 13
Open Access | Times Cited: 8
Functional network: A novel framework for interpretability of deep neural networks
Ben Zhang, Zhetong Dong, Junsong Zhang, et al.
Neurocomputing (2022) Vol. 519, pp. 94-103
Open Access | Times Cited: 8
Predicting the generalization gap in neural networks using topological data analysis
Rubén Ballester, Xavier Arnal Clemente, Carles Casacuberta, et al.
Neurocomputing (2024) Vol. 596, pp. 127787-127787
Open Access | Times Cited: 1
Towards Understanding Graph Neural Networks: Functional-Semantic Activation Mapping
Kislay Raj, Alessandra Mileo
Lecture notes in computer science (2024), pp. 98-106
Closed Access | Times Cited: 1
Edge detection and graph neural networks to classify mammograms: A case study with a dataset from Vietnamese patients
Linh T. Duong, Cong Q. Chu, Phuong T. Nguyen, et al.
Applied Soft Computing (2022) Vol. 134, pp. 109974-109974
Closed Access | Times Cited: 7
Functional Semantics Analysis in Deep Neural Networks
Ben Zhang, Gengchen Li, Hongwei Lin
Communications in computer and information science (2024), pp. 232-243
Closed Access
A comprehensive review of deep neural network interpretation using topological data analysis
Ben Zhang, Zitong He, Hongwei Lin
Neurocomputing (2024) Vol. 609, pp. 128513-128513
Closed Access
Towards a neuro-symbolic cycle for human-centered explainability
Alessandra Mileo
Deleted Journal (2024), pp. 1-13
Open Access
Avaliação da presença de fissuras em imagens de estruturas de concreto através do uso de redes neurais profundas
Wanderlei Malaquias Pereira, Sérgio Silva, Alessandro Rodrigues e Silva, et al.
Matéria (Rio de Janeiro) (2024) Vol. 29, Iss. 4
Open Access
Finding Concept Representations in Neural Networks with Self-Organizing Maps
Mathieu d’Aquin
(2023), pp. 53-60
Open Access | Times Cited: 1
Special Issue on Machine Learning and Knowledge Graphs
Mehwish Alam, Dieter Fensel, Jorge Martinez‐Gil, et al.
Future Generation Computer Systems (2021) Vol. 129, pp. 50-53
Open Access | Times Cited: 3
Generating Local Textual Explanations for CNNs: A Semantic Approach Based on Knowledge Graphs
Vitor Horta, Alessandra Mileo
Lecture notes in computer science (2022), pp. 532-549
Closed Access | Times Cited: 2
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
Felix Hensel, Charles Arnal, Mathieu Carrière, et al.
arXiv (Cornell University) (2023)
Open Access
Knowledge Extraction from Auto-Encoders on Anomaly Detection Tasks Using Co-activation Graphs
Daniyal Selani, Ilaria Tiddi
(2021), pp. 65-71
Open Access
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