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"
A deterministic algorithm for Symbolic Regression, which I recently ported to JAX
(original post refreshed by HN mods if I understand correctly, maybe dang or tomhow will chime in on this)