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4 Graph Neural Networks you Need to Know (WLG, GCN, GAT, GIN)
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4 Graph Neural Networks you Need to Know (WLG, GCN, GAT, GIN)

Last Updated on July 20, 2023 by Editorial Team

Author(s): Edward Ma

Originally published on Towards AI.

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Photo by Edward Ma on Unsplash

We went through Knowledge Graph Embeddings and Random Walk in previous graph neural network stories. Knowledge graph embeddings train entity embeddings for downstream tasks. On the other hand, several neural networks model apply random walk theory to train entity embeddings.

In this story, we will go focus on 4 graph neural network models which are Weisfeiler-Lehman Graph Kernel (Shervashidze et al., 2011), Graph Convolutional Network (Kipf and Welling, 2017), Graph Attention Networks (VeličkoviΔ‡ et al., 2017) and Graph Isomorphism Network (Xu et al., 2019)

Shervashidze et al. (2011) introduce a way to measure graph similarity (WL… Read the full blog for free on Medium.

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