Graph Attention Networks (GAT) in 5 minutes

What's the significant difference between Relational GCN & graph attention network ? is it the concatenation and the dot product of a ? coz I saw both are also assigned with different weights

Fantastic

I like you videos. Easy to understand with the essential things revealed

Just excellent.

please answer me. did GAT considered as a variant of GCNs ?

Incredible video. Super well explained and much better than how university taught it
=

Great video!

Wouldn't concatination of multiple head results lead to exponentially growing node representation with regards to the number of gat layers?

Thank you!

Out of curiosity, what are your thoughts on combining RGCNs with GATs, as in, instead of regular degree based aggregations in RGCNs for each Relation, what do you think of calculating an attention based weight in the formula?

What is the link to the first video for Graph NNs?

Hi hope you're doing well
Is there any graph neural network architecture that receives multivariate dataset instead of graph-structured data as an input?
I'll be very thankful if you answer me i really nead it
Thanks in advanced

awesome content! thank you!

This is top notch stuff. I'm trying to leverage my biophysics background for a GNN-related project, and this channel is kinda my go-to for concepts. Wanted to take your course, but being a grad student in a third-world country, and when the conversion rate kicks in, it gets out of reach :/

Great overview, thanks. What does the T in GAT stand for?

well explained...

Great! .. I really like your explanation .. we need more, please

Brief explanation for GAT. Thanks alot. This is currently what I need for thesis