Why does every graph of neural networks always illustrate a layer of neurons only communicating forward by *one* layer of neurons instead of multiple layers forward simultaneously?

Question

Why does every graph of neural networks always illustrate a layer of neurons only communicating forward by *one* layer of neurons instead of multiple layers forward simultaneously?

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Answer 1

The key word here is “illustrate”. They want be able to introduce the concept in a way that is easy to understand and doesn’t result in much confusion. Showing a network with a more complex interrelationship between layers is just going to make understanding a hard ideal even worse.

Now, mechanically most neural networks layers are implemented as matrices, and their communication is done through matrix multiplication, communication through multiple isn’t really possible. Instead, you create a dummy node that exists just to pass through the value unchanged from one layer to the next. From a technical standpoint, any design with communication between multiple layers can be implements using communication between single layers.