Symbolic Learning in Python and Julia

 (github.com)

53 points | by alex_hirner 4 days ago

6 comments

  • owls-on-wires 27 minutes ago
    related: https://github.com/owls-on-wires/keplearn

    A deterministic SR engine in Rust, written for SRBench. Happy to see the field getting some front-page attention!

  • brumar 1 hour ago
    How do we measure and compare prediction quality in a symbolic/deterministic context that also punish for complexity? I struggled on this in my phd thesis and had to brew my own Minimum Description Length implementation because I found nothing applicable. The statisticians I interrogated were like "don't try to do model selection on symbolic models, make them probabilistic and work from there"
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  • JanisErdmanis 1 hour ago
    Is the Julia part here compiled via JuliaC and if not what would it take to do so?
  • jgalt212 57 minutes ago
    Has anyone thrown the n-body problem at this?
  • verdverm 4 days ago
    related: https://github.com/verdverm/pge-jax

    A deterministic algorithm for Symbolic Regression, which I recently ported to JAX

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    • verdverm 4 hours ago
      weird that my comment time was updated, this was not today

      (original post refreshed by HN mods if I understand correctly, maybe dang or tomhow will chime in on this)

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      • Jtsummers 4 hours ago
        Second chance pool. All comments get a new timestamp with the submission for a while. Eventually it will have its original timestamp.
  • thatsabadlook 4 hours ago
    Yay now when you load your python project you have 2 interpreters, 2 gcs, 200mb of ram overhead, and nondeterministic performance due to joat.