all AI news
Graph Neural Networks: Taxonomy, Advances and Trends. (arXiv:2012.08752v3 [cs.LG] UPDATED)
Jan. 24, 2022, 2:10 a.m. | Yu Zhou, Haixia Zheng, Xin Huang, Shufeng Hao, Dengao Li, Jumin Zhao
cs.LG updates on arXiv.org arxiv.org
Graph neural networks provide a powerful toolkit for embedding real-world
graphs into low-dimensional spaces according to specific tasks. Up to now,
there have been several surveys on this topic. However, they usually lay
emphasis on different angles so that the readers can not see a panorama of the
graph neural networks. This survey aims to overcome this limitation, and
provide a comprehensive review on the graph neural networks. First of all, we
provide a novel taxonomy for the graph neural …
arxiv graph graph neural networks networks neural networks taxonomy trends
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
(373) Applications Manager – Business Intelligence - BSTD
@ South African Reserve Bank | South Africa
Data Engineer Talend (confirmé/sénior) - H/F - CDI
@ Talan | Paris, France
Data Science Intern (Summer) / Stagiaire en données (été)
@ BetterSleep | Montreal, Quebec, Canada
Director - Master Data Management (REMOTE)
@ Wesco | Pittsburgh, PA, United States
Architect Systems BigData REF2649A
@ Deutsche Telekom IT Solutions | Budapest, Hungary
Data Product Coordinator
@ Nestlé | São Paulo, São Paulo, BR, 04730-000