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submitted 10 months ago by throws_lemy@lemmy.nz to c/technology@lemmy.world
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[-] Aatube@kbin.social 12 points 10 months ago
  1. Specifying weights, biases and shape definitely makes a graph.
  2. IMO having a lot of more preferred and more deprecated routes is quite close to a flowchart except there's a lot more routes. The principles of how these work is quite similar.
[-] General_Effort@lemmy.world -1 points 10 months ago
  1. There are graph neural networks (meaning NNs that work on graphs), but I don't think that's what is used here.

  2. I do not understand what you mean by "routes". I suspect that you have misunderstood something fundamental.

[-] Aatube@kbin.social 3 points 10 months ago
  1. I'm not talking about that. What's weights, biases and shape if not a graph?
  2. By routes, I mean that the path of the graph doesn't necessarily converge and that it is often more tree-like.
[-] General_Effort@lemmy.world 3 points 10 months ago* (last edited 10 months ago)

You can see a neural net as a graph in that the neurons are connected nodes. I don't believe that graph theory is very helpful, though. The weights are parameters in a system of linear equations; the numbers in a matrix/tensor. That's not how the term is used in graph theory, AFAIK.

ETA: What you say about "routes" (=paths?) is something that I can only make sense of, if I assume that you misunderstood something. Else, I simply don't know what that is talking about.

[-] Natanael@slrpnk.net 2 points 10 months ago

If you look at the nodes which are most likely to trigger from given inputs then you can draw paths

[-] General_Effort@lemmy.world 2 points 10 months ago

I still don't know what this is supposed to mean for neural nets. I think it reflects a misunderstanding.

this post was submitted on 13 Feb 2024
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