The article seems to be a bit light on details for an "overview" of GNNs.

It's an area I've recently been researching and they do seem to be gaining a significant amount of traction. If anyone is interested in additional reading material, I can suggest the very recent GNNs: Models and Applications (slide deck available on the website) [0].

There is also a fairly comprehensive GitHub repo on [1], though I personally haven't given it a detailed look yet.

[0] http://cse.msu.edu/~mayao4/tutorials/aaai2020/

[1] https://github.com/benedekrozemberczki/awesome-graph-classif...