#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED] - podcast episode cover

#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]

Mar 25, 20221 hr 3 minSeason 1Ep. 71
--:--
--:--
Download Metacast podcast app
Listen to this episode in Metacast mobile app
Don't just listen to podcasts. Learn from them with transcripts, summaries, and chapters for every episode. Skim, search, and bookmark insights. Learn more

Episode 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)


Want to sponsor MLST!? Let us know on Linkedin / Twitter. 


[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)

For the best experience, listen in Metacast app for iOS or Android
Open in Metacast
#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED] | Machine Learning Street Talk (MLST) podcast - Listen or read transcript on Metacast