@@DeepFindr I do a lot of machine learning for my work and I’ve recently thought about modelling train networks as a graph to apply algorithms. d’you have a discord or something, would love to chat a bit?
I am looking forward to present a lecture based in dynamic graphs variational autoencoder where temporal dependencies occured in dataset such as autonomous driving for point clouds change at each time instant,also to get latent space Z. Please read a paper joint dynamic variational graph autoencoder and make a video on its implementation step by step. I will be very thankful
You can search VGRNN(Variational Graph Recurrent Neural Network) which is handling dynamic graph by snapshot. It means that sequences graph (=dynamic graph) can see multi-static graph. This method called discrete method.
This video is exactly what I was looking for! Great summary.
Amazing video! Thanks for the great work.
Banger vid from big dog as always🐶
bro your channel is insane!
Haha thanks! Glad you like it
@@DeepFindr I do a lot of machine learning for my work and I’ve recently thought about modelling train networks as a graph to apply algorithms. d’you have a discord or something, would love to chat a bit?
Hi! I'd love to but unfortunately I don't find time to maintain a discord or anything like that. Maybe in the future :)
Great channel! Keep up the good work!
Ur work is appreciable sir pls upload next video and also make the movie recommender system code explanation
Hmm can make something on solving NP hard combinatorial graph problems using GNNs?
You are incredible
Thanks for really great videos! Could you please create a video on temporal variational graph autoencoders?
Do you know any libraries implementing self supervised learning on graphs?
I am looking forward to present a lecture based in dynamic graphs variational autoencoder where temporal dependencies occured in dataset such as autonomous driving for point clouds change at each time instant,also to get latent space Z. Please read a paper joint dynamic variational graph autoencoder and make a video on its implementation step by step. I will be very thankful
You can search
VGRNN(Variational Graph Recurrent Neural Network) which is handling dynamic graph by snapshot. It means that sequences graph (=dynamic graph) can see multi-static graph. This method called discrete method.
Can show some demos on google colab, are there any more applications ?
Will do a contrastive tutorial with code soon :) what kind of applications do you mean?
Hello,
Do you think Generative Adversarial Networks can improve the performance of GCN . if that so how it work?/
Yes
No
@@washedtoohot so yes or no ?
Great as always :D
Amazing video. What tool do you use to make the slides and the beautiful graphics?
Thanks :) DaVinci resolve and PowerPoint :P