Introduction to graph neural networks (made easy!)

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Graph machine learning has become very popular in recent years in the machine learning and engineering communities. In this video, we explore the math behind some of the most popular graph neural network algorithms!

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Jacob Heglund

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Hope there will be more videos about GNNs, would love to see a variety of real problems being represented by Graphs and solved using GNNs!

bnjmn

Amazing explanation, was reading about GNN's for an intern assignment
Thanks !

newbie

Very nice video with such easily understandable explanation of such complex concepts, thank you. I don't know why you stopped making videos, you are good at them, I watched all four of your videos

prachikgp

Incredible explanation! You made it simple to the point.

ScienceMasterHK

Thanks for the cool explanation! Subscribed👍🏻

ShikhaMallick

my first impression is "what a nice background ambiance. thanks for the topic and level.

mikeCavalle

Thanks for this, I'm using this to help a student with a GNN journal publication.

draziraphale

Thanks for putting the effort into this well made video! Was very helpful

TheVishnu

Awesome video and explanations! So many good resources to check out, thank you for making this! Looking forward to more

thousandTabs

Great content!! Greetings from Germany

christiansinger

WE WANT MORE!!! 1yr is too long a wait

Septumsempra

Pretty great! I would love to see some example applications of these models in a future video. Subscribed!

amanrv

Wonderful video jacob, Please also make a video on implementing GNNS, GATs on Pytorch /TensorFlow and explain how math works in code .It would be really helpful

MahimDashoraHackR

Sorry to me GNN are “just” being selective about how to connect one layer to the next through the adjacency matrix. We simplify the basic dense layer system which then enables fast convergence of the network… right? Conv nets do the same. They establish a neighborhood to each input.
So if previous approaches do not leverage this inherent structure in the data, they cant do as well.
Let me know if I m missing something.

sunaxes

Surely k is not the number of hops? From the paper it says "We use superscripts to distinguish the embeddings and
functions at different iterations of message passing."

pennyfarthingchapel

at 3:41 shouldn't it be "l" instead of "k"? I mean it should be a layer, not hop (the previous layer will affect the next layer)

mrigankanath

Thanks. Can you make a practical video on how to generate a GNN.

milandoshi

Great content! Hope to see more videos.. Can you make videos with real world examples.. with code..

vijayrameshkumar

How is GNN better than the BoW algorithm?

ThankYouESM

So I clicked on the link to the first video on graph neural networks and it took me right back to the Second video. Bad graph 😃

cybervigilante

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