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Home > Machine Learning Street Talk > #71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]
Podcast: Machine Learning Street Talk
Episode:

#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]
Category: Technology
Duration: 01:02:35
Publish Date: 2022-03-25 18:10:05
Description:

Special discount link for Zak's GNN course - https://bit.ly/3uqmYVq

Patreon: https://www.patreon.com/mlst

Discord: https://discord.gg/ESrGqhf5CB

YT version: https://youtu.be/jAGIuobLp60 (there are lots of helper graphics there, recommended if poss)


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[00:00:00] Preamble

[00:03:12] Geometric deep learning

[00:10:04] Message passing

[00:20:42] Top down vs bottom up

[00:24:59] All NN architectures are different forms of information diffusion processes (squashing and smoothing problem)

[00:29:51] Graph rewiring

[00:31:38] Back to information diffusion 

[00:42:43] Transformers vs GNNs

[00:47:10] Equivariant subgraph aggregation networks + WL test

[00:55:36] Do equivariant layers aggregate too?

[00:57:49] Zak's GNN course


Exhaustive list of references on the YT show URL (https://youtu.be/jAGIuobLp60)
Total Play: 0