• Aatube@kbin.social
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    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
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      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
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        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
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          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
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            10 months ago

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