Machine Learning Street Talk (MLST) artwork

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

Machine Learning Street Talk (MLST)

English - March 25, 2022 18:10 - 1 hour - 86 MB
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Previous Episode: #70 - LETITIA PARCALABESCU - Symbolics, Linguistics [UNPLUGGED]
Next Episode: #72 Prof. KEN STANLEY 2.0 - On Art and Subjectivity [UNPLUGGED]

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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)