Graph Neural Network - Part-1

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This tutorial Contains.
1. Why Graph Neural Networks??
2. Limitations of Current Architectures.
References:
1. Hamilton et al. 2017. Representation Learning on Graphs: Methods
and Applications. IEEE Data Engineering Bulletin on Graph Systems.
2. Scarselli et al. 2005. The Graph Neural Network Model. IEEE
Transactions on Neural Networks.
3. Kipf et al., 2017. Semisupervised Classification with Graph Convolutional
Networks. ICLR.
4. Hamilton et al., 2017. Inductive Representation Learning on Large Graphs.
NIPS.

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Комментарии

Thanks but have question from where you the feature come why 0001 and 111 why

البداية-ذذ

Could you please tell me, why we do embedding, is it for feature extraction for machine learning or what for, or it uses directly for node classification?

mohamadabdulkarem

why addition or deletion node is beneficial in graph architecture? Can you please explain

maulikmadhavi

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