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A Gentle Introduction to Graph Neural Networks (2021)

(distill.pub)
354 points misonic | 1 comments | 20 Dec 24 04:10 UTC | HN request time: 0.203s | source
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openrisk ◴[20 Dec 24 12:48 UTC] No.42470663[source]▶
Very high quality work, its a pity that distill.pub did not find a sustainable way forward [1].

On GNN's, the lack of datasets [2] might be a reason they are not as talked about. This is something that has affected also the semantic web domain.

[1] https://distill.pub/2021/distill-hiatus/

[2] https://huggingface.co/datasets?task_categories=task_categor...

replies(2): >>42471681 #>>42473792 #
1. wenc ◴[20 Dec 24 18:59 UTC] No.42473792[source]▶
My personal hack is that before jumping into papers in unfamiliar areas like these, I go on YouTube and search for “<topic> explained”.

The power of YouTube is that for any hot area, there are a bunch of people incentivized to make a short video that maximally engages. The quality can be quite high even at higher levels of math abstractions. The visuals are really helpful to get a feel for the abstractions (3 blue 1 brown proved this years ago).

There are some excellent videos of GNNS that in less than 10 mins gave me a launching point into the literature.