Graph Neural Network: A Comprehensive Review on Non-Euclidean Space

Graph Neural Network: A Comprehensive Review on Non-Euclidean Space

This review provides a comprehensive overview of the state-of-the-art methods of graph-based networks from a deep learning perspective. Graph networks provide a generalized form to exploit non-euclidean space data. A graph can be visualized as an aggregation of nodes and edges without having any ord...

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Détails bibliographiques
Auteurs principaux: Nurul A. Asif, Yeahia Sarker, Ripon K. Chakrabortty, Michael J. Ryan, Md. Hafiz Ahamed, Dip K. Saha, Faisal R. Badal, Sajal K. Das, Md. Firoz Ali, Sumaya I. Moyeen, Md. Robiul Islam, Zinat Tasneem
Format: Article
Langue:English
Publié: IEEE 2021-01-01
Collection:IEEE Access
Sujets:
Graph neural network
geometric deep learning
graph-structured network
non-euclidean space
Accès en ligne:https://ieeexplore.ieee.org/document/9395439/

Internet

https://ieeexplore.ieee.org/document/9395439/

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