Excellent video. I hadn't come across the Relational Deep Learning' paper where data-mining use case of taking relational tables as input. Genius idea.
Thank you! Indeed, that research came out just a couple of months ago and may unlock so many exciting applications because of its great generality and applicability!
Graphs can be easily described with sparse matrices, so GNN are not something very special. More tricks are about dataset preparations for their tuning.
Amazing video, one of the best intro to GNNs on YT. Thank you!
Glad you liked it!
Excellent video. I hadn't come across the Relational Deep Learning' paper where data-mining use case of taking relational tables as input. Genius idea.
Thank you! Indeed, that research came out just a couple of months ago and may unlock so many exciting applications because of its great generality and applicability!
Fantastic video. So much information!
Glad it was helpful!
Thanks for the overview, helped a ton. Would love to see videos diving into GNN architecture
Nice video ! One could also talk about the incorporation of the powerful transformers architecture into GNN
Excellent! Very clear, very much well conceived and structured; understendable also by non-experts.
Thank you. I have a node/edge graph problem and i need to get smart on GNN in a hurry.🙏🏽
You're welcome and good luck!
Great video, thank you 😊
Thanks, a good introduction! A friendly comment, there is some dirt on your camera. Looking forward to studying GNNs
Thanks for watching!
need a separate Video for GNN
can we use a graph transformer in a relational database for the research point of view?
I found the dirt on the camera in the center of the screen very distracting. Perhaps you can use AI to remove it 😀
don't be dramatic, it's a snot not a dirt
Graphs can be easily described with sparse matrices, so GNN are not something very special. More tricks are about dataset preparations for their tuning.
😎🤖
If you know good video on explaining what GraphNN are, please share. This video requires to know the basics of GNN.