[Deep Graph Learning] 3.3 Graph pooling & embedding aggregation

#DGL #GCN #GNN
📚🔗 The CLEAN summary map of the DGL videos 3.1 to 3.5 can be found at: https://drive.google.com/file/d/1p7U1xyW4-5W4ge8gRstUkBGQSY3fKHX6/view?usp=sharing

📚🔗 The ANNOTATED summary map of the DGL videos 3.1 to 3.5 can be found at: https://drive.google.com/file/d/1Jf5YiYycm6IBzLtOsF1yUsCX8bQWodv4/view?usp=sharing

Unlock the world of Deep Graph Learning with our new video series!
🚀 Dive into the mathematical foundations of graph neural networks using an intuitive approach and the power of linear algebra.

👉 Extra resources and tutorials:
1) Graph convolutional neural networks https://mbernste.github.io/posts/gcn
2) A Gentle Introduction to Graph Neural Networks https://distill.pub/2021/gnn-intro
3) Graph Convolutional Networks https://tkipf.github.io/graph-convolutional-networks/

Special thanks to Simon Prince, Alex Fornito, Andrew Zalesky, Edward Bullmore, Jure Leskovec and all those who shared their passion about graphs and deep learning.
Textbooks:
• Simon Prince; Understanding Deep Learning (2023); https://github.com/udlbook/
• Bullmore, Edward T., Fornito, Alex, and Zalesky, Andrew; Fundamentals of Brain Network Analysis-Academic Press, Elsevier (2016)

Видео [Deep Graph Learning] 3.3 Graph pooling & embedding aggregation канала BASIRA Lab