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Jax implementation of the PGE algorithm (Prioritized Grammar Enumeration)

2 starsPython

Modernizing my old PhD work in an evening with little Qwen3.6 MoE

by verdverm·May 21, 2026·3 points·0 comments

AI Analysis

●●●BangerBig BrainWizardry

Pure JAX pipeline enables GPU acceleration where previous Python implementations stalled.

Strengths
  • Replaces slow CPU-bound evaluation with JIT-compiled JAX operations for massive speedups.
  • Implements multi-objective Pareto front selection without external ML dependencies.
  • Automatic differentiation handles Jacobian computation internally for gradient optimization.
Weaknesses
  • Niche academic algorithm limits appeal to general machine learning practitioners.
  • Documentation assumes familiarity with symbolic regression concepts and grammar rules.
Category
Target Audience

Data scientists and researchers in symbolic regression

Similar To

gplearn · PySR · pypge

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