Wow, this article came up at the time and in 2017. And I even see a little comment I wrote back then in the helpful link dang provided. It looks very different

Wow, this article came up at the time and in 2017. And I even see a little comment I wrote back then in the helpful link dang provided. It looks very different to me now than then. Mostly because for various reasons I actually know what all those networks are. And a fair percentage aren't normally considered neural networks at all (Belief networks, Markov Chains...). Other models are quite old (Kohonen networks, so old I studied them at school in the 90s), other things very broad categories that other classes may or may not fit into (feed forward network, autoencoder). So the categories are essentially an incoherent mess or a useful cheat sheet for going through the literature, take your pick. I see this now, where back then I just saw an impressive/incoherent mess and that makes me feel like maybe I'm learning something in my personal research project.