SymbolicRegression.jl and PySR

The tools are competitors, with MilesCranmer/PySR being a more recent, multi-language symbolic regression framework that aims to improve upon and potentially supersede specialized Julia implementations like astroautomata/SymbolicRegression.jl.

SymbolicRegression.jl
65
Established
PySR
63
Established
Maintenance 17/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 17/25
Adoption 10/25
Maturity 16/25
Community 20/25
Stars: 771
Forks: 123
Downloads: —
Commits (30d): 9
Language: Julia
License: Apache-2.0
Stars: 3,427
Forks: 315
Downloads: —
Commits (30d): 8
Language: Python
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About SymbolicRegression.jl

astroautomata/SymbolicRegression.jl

Distributed High-Performance Symbolic Regression in Julia

This project helps scientists and researchers discover underlying mathematical equations from observational data. You input a dataset of numerical observations, and it outputs potential mathematical formulas that describe the relationships within your data, such as `2 * cos(x1) - x2^2`. It is used by anyone who needs to find simple, explainable models from complex data, particularly in scientific fields.

scientific-modeling equation-discovery data-analysis physics chemistry

About PySR

MilesCranmer/PySR

High-Performance Symbolic Regression in Python and Julia

This tool helps scientists, engineers, and researchers discover the underlying mathematical equations that describe their data. You input your experimental or observational data (features and target values), and it outputs a list of simple, interpretable formulas that fit your data well. This is perfect for anyone trying to understand the fundamental relationships within their measurements rather than just predicting outcomes.

scientific-modeling physics-discovery data-analysis equation-discovery interpretable-AI

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