• Aatube@kbin.social
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      9 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
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        9 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
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          9 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
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            9 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
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              9 months ago

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