Unlocking the Potential of Message Passing: Exploring GraphSAGE, GCN and GAT | GNN GraphML
Ғылым және технология
Introduction to GRAPH ML, Graph Neural Networks (GNN) and the main idea behind Message Passing in graph network configurations of GraphSAGE, GCN and GAT.
Message passing applied to Graph Convolutional Networks (GCN), GraphSAGE and Graph Attention Networks. The key difference between GAT and GCN is how the information from the k-hop neighborhood is aggregated.
Stanford online: CS224W
• Stanford CS224W: Machi...
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Пікірлер: 9
Thank you I just found your channel and I'm enjoy ing your explanations very much. Many of these concepts I never expected I'd understand as well as I do from watching your videos.
@code4AI
8 ай бұрын
You're very welcome!
Thank you!! Everything is so clear!!
Thank you :) Nice explanation
@code4AI
Жыл бұрын
Glad it was helpful!
your dry humor kills me "so the node embedding of node v is h(v), congratulations" 😂
@code4AI
Жыл бұрын
Finally someone appreciates my humor! Thank you!
Can you create a video on edge classification for heterogeneous graphs
@code4AI
Жыл бұрын
Yes, of course. This topic is now in my pipeline, since I'll do a mini-series to code in detail Graph ML topics. Thank you for your comment.