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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:

GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes
Megi Isallari, Islem Rekik
Lecture notes in computer science (2020), pp. 139-149
Closed Access | Times Cited: 11

Showing 11 citing articles:

Graph Neural Networks in Network Neuroscience
Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik
IEEE Transactions on Pattern Analysis and Machine Intelligence (2022) Vol. 45, Iss. 5, pp. 5833-5848
Open Access | Times Cited: 165
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4758-4758
Open Access | Times Cited: 159
Replica-Based Federated Learning with Heterogeneous Architectures for Graph Super-Resolution
Ramona Ghilea, Islem Rekik
Lecture notes in computer science (2023), pp. 273-282
Closed Access | Times Cited: 3
StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis
Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik
Lecture notes in computer science (2021), pp. 140-150
Open Access | Times Cited: 4
Diffusion-Based Graph Super-Resolution with Application to Connectomics
Nishant Rajadhyaksha, Islem Rekik
Lecture notes in computer science (2023), pp. 96-107
Closed Access | Times Cited: 1
Deep Cross-Modality and Resolution Graph Integration for Universal Brain Connectivity Mapping and Augmentation
Ece Çınar, Sinem Elif Haseki, Alaa Bessadok, et al.
Lecture notes in computer science (2022), pp. 89-98
Closed Access | Times Cited: 2
A Review of Super Resolution Based on Deep Learning
Qingyang Chen, Zhenping Qiang, Hong Lin
(2022)
Closed Access | Times Cited: 1
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain Connectivity
Megi Isallari, Islem Rekik
arXiv (Cornell University) (2021)
Closed Access
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping
Islem Mhiri, Ahmed Nebli, Mohamed Ali Mahjoub, et al.
arXiv (Cornell University) (2021)
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
StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis
Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik
arXiv (Cornell University) (2021)
Closed Access
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