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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:

Brain graph super-resolution using adversarial graph neural network with application to functional brain connectivity
Megi Isallari, Islem Rekik
Medical Image Analysis (2021) Vol. 71, pp. 102084-102084
Open Access | Times Cited: 14

Showing 14 citing articles:

Generative AI for brain image computing and brain network computing: a review
Changwei Gong, Changhong Jing, Xuhang Chen, et al.
Frontiers in Neuroscience (2023) Vol. 17
Open Access | Times Cited: 53
A Systematic Review of Graph Neural Network in Healthcare-Based Applications: Recent Advances, Trends, and Future Directions
Showmick Guha Paul, Arpa Saha, Md. Zahid Hasan, et al.
IEEE Access (2024) Vol. 12, pp. 15145-15170
Open Access | Times Cited: 17
A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD
Kanhao Zhao, Boris Duka, Hua Xie, et al.
NeuroImage (2021) Vol. 246, pp. 118774-118774
Open Access | Times Cited: 91
Aim-based choice of strategy for MEG-based brain state classification
Irina Saranskaia, Boris Gutkin, Denis Zakharov
The European Physical Journal Special Topics (2025)
Closed Access
LCRCA: image super-resolution using lightweight concatenated residual channel attention networks
Changmeng Peng, Pei Shu, Xiaoyang Huang, et al.
Applied Intelligence (2022) Vol. 52, Iss. 9, pp. 10045-10059
Closed Access | Times Cited: 17
A comprehensive survey of complex brain network representation
Haoteng Tang, Guixiang Ma, Yanfu Zhang, et al.
Meta-Radiology (2023) Vol. 1, Iss. 3, pp. 100046-100046
Open Access | Times Cited: 10
Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image
Xiao Xiao, Yan Kong, Rong-Han Li, et al.
Medical Image Analysis (2023) Vol. 91, pp. 103040-103040
Open Access | Times Cited: 8
A Survey of GNN in Bioinformation Data
Zhenyi Zhu
(2022)
Open Access | Times Cited: 4
Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network
Y Hu, Junling Ran, Rui Qiao, et al.
Neural Plasticity (2024) Vol. 2024, pp. 1-14
Open Access
Strongly Topology-Preserving GNNs for Brain Graph Super-Resolution
Pragya Singh, Islem Rekik
Lecture notes in computer science (2024), pp. 124-136
Closed Access
Inter-domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning
Başar Demir, Alaa Bessadok, Islem Rekik
Lecture notes in computer science (2021), pp. 203-215
Closed Access | Times Cited: 1
Research on the Application of Graph Neural Networks in Financial Asset Valuation
Yuge Song, Zerui He
(2023), pp. 27-31
Closed Access
Predicting Brain Multigraph Population from a Single Graph Template for Boosting One-Shot Classification
Furkan Pala, Islem Rekik
Lecture notes in computer science (2022), pp. 191-202
Closed Access
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning.
Basar Demir, Alaa Bessadok, Islem Rekik
arXiv (Cornell University) (2021)
Closed Access
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