Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020

Graph structured data is ubiquitous in daily life and scientific areas and has attracted increasing attention. Graph Neural Networks (GNNs) have been proved to be effective in modeling graph structured data and many variants of GNN architectures have been proposed. However, much human effort is ofte...

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Detalles Bibliográficos
Autores principales: Xu, Zhen, Wei, Lanning, Zhao, Huan, Ying, Rex, Yao, Quanming, Tu, Wei-Wei, Guyon, Isabelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245425/
https://www.ncbi.nlm.nih.gov/pubmed/35783353
http://dx.doi.org/10.3389/frai.2022.905104

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245425/
https://www.ncbi.nlm.nih.gov/pubmed/35783353
http://dx.doi.org/10.3389/frai.2022.905104

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