AI News, Concise Visual Summary of Deep Learning Architectures

Concise Visual Summary of Deep Learning Architectures

This article was written by Fjodor Van Veen.  With new neural network architectures popping up every now and then, it’s hard to keep track of them all.

Though all of these architectures are presented as novel and unique, when I drew the node structures… their underlying relations started to make more sense.

I should add that this overview is in no way clarifying how each of the different node types work internally (but that’s a topic for another day).

That’s not the end of it though, in many places you’ll find RNN used as placeholder for any recurrent architecture, including LSTMs, GRUs and even the bidirectional variants.

Many abbreviations also vary in the amount of “N”s to add at the end, because you could call it a convolutional neural network but also simply a convolutional network (resulting in CNN or CN).

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