Papers › Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl

Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl

2 May 2023arXiv:2305.01582archive 2025-07-28

Miles Cranmer

PySR is an open-source library for practical symbolic regression, a type of machine learning which aims to discover human-interpretable symbolic models. PySR was developed to democratize and popularize symbolic regression for the sciences, and is built on a high-performance distributed back-end, a flexible search algorithm, and interfaces with several deep learning packages. PySR's internal search algorithm is a multi-population evolutionary algorithm, which consists of a unique evolve-simplify-optimize loop, designed for optimization of unknown scalar constants in newly-discovered empirical expressions. PySR's backend is the extremely optimized Julia library SymbolicRegression.jl, which can be used directly from Julia. It is capable of fusing user-defined operators into SIMD kernels at runtime, performing automatic differentiation, and distributing populations of expressions to thousands of cores across a cluster. In describing this software, we also introduce a new benchmark, "EmpiricalBench," to quantify the applicability of symbolic regression algorithms in science. This benchmark measures recovery of historical empirical equations from original and synthetic datasets.

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MilesCranmer/PySR officialmentioned in papermentioned on GitHubpytorchApache-2.0 report
milescranmer/pysr_paper officialmentioned in papermentioned on GitHub report
milescranmer/symbolicregression.jl officialmentioned in papermentioned on GitHubApache-2.0 report
hftsoi/symbolfit mentioned on GitHubMIT report

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1ran · honoured contract
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exec_then_eval milescranmer/pysr_paper/src/scripts/benchmark.py official repository ran · honoured contract MIT (permissive) · dbaba5d6f75f42b2 · report
gen_dataset_using_generator milescranmer/pysr_paper/src/scripts/benchmark.py official repository ran · our draft was wrong MIT (permissive) · f6c7138e24af8065 · report
denoise MilesCranmer/PySR/pysr/denoising.py official repository unverified Apache-2.0 (permissive) · 2e8d4f68018bb06b · report
generate_table_environment MilesCranmer/PySR/pysr/export_latex.py official repository unverified Apache-2.0 (permissive) · 35cac027aec2fc9a · report
go_to_level milescranmer/symbolicregression.jl/benchmark/analyze.py official repository unverified Apache-2.0 (permissive) · 425b9408358a1729 · report
isinstalled MilesCranmer/PySR/pysr/julia_extensions.py official repository unverified Apache-2.0 (permissive) · 6ddcd76b319a6e15 · report
load_package MilesCranmer/PySR/pysr/julia_extensions.py official repository unverified Apache-2.0 (permissive) · 748684a68ada334b · report
load_pysr_graph milescranmer/symbolicregression.jl/benchmark/family_tree.py official repository unverified Apache-2.0 (permissive) · 787326048f48a5af · report
multi_denoise MilesCranmer/PySR/pysr/denoising.py official repository unverified Apache-2.0 (permissive) · 788c8f857dfc7e08 · report
pysr MilesCranmer/PySR/pysr/deprecated.py official repository unverified Apache-2.0 (permissive) · 6f4e50a90f40bacf · report
run_feature_selection MilesCranmer/PySR/pysr/feature_selection.py official repository unverified Apache-2.0 (permissive) · e6060650fde67a36 · report
simplify_graph milescranmer/symbolicregression.jl/benchmark/family_tree.py official repository unverified Apache-2.0 (permissive) · d9fc600105551ba1 · report
sympy2jax MilesCranmer/PySR/pysr/export_jax.py official repository unverified Apache-2.0 (permissive) · 2b540eef802dcbec · report
sympy2jaxtext MilesCranmer/PySR/pysr/export_jax.py official repository unverified Apache-2.0 (permissive) · 7dcdebb05351545b · report
sympy2latex MilesCranmer/PySR/pysr/export_latex.py official repository unverified Apache-2.0 (permissive) · 2f9e8a418b2ddf46 · report
sympy2latextable MilesCranmer/PySR/pysr/export_latex.py official repository unverified Apache-2.0 (permissive) · 87522bac09e9f038 · report
sympy2numpy MilesCranmer/PySR/pysr/export_numpy.py official repository unverified Apache-2.0 (permissive) · 550105efb9068877 · report
sympy2torch MilesCranmer/PySR/pysr/export_torch.py official repository unverified Apache-2.0 (permissive) · 4da53042a817d8dd · report
add_gof hftsoi/symbolfit/symbolfit/evaluate.py community (archive-listed) unverified MIT (permissive) · 33cebf0739d3fc8e · report
cond hftsoi/symbolfit/symbolfit/math_defs.py community (archive-listed) unverified MIT (permissive) · 7339ce430d9364c3 · report
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histogram_scale hftsoi/symbolfit/symbolfit/processing.py community (archive-listed) unverified MIT (permissive) · 009111bb1da07095 · report
piecewise hftsoi/symbolfit/symbolfit/math_defs.py community (archive-listed) unverified MIT (permissive) · d09001cea2cb6d5d · report
round_a_number hftsoi/symbolfit/symbolfit/utils.py community (archive-listed) unverified MIT (permissive) · 8835c31e0f902ddc · report
round_numbers_in_sympy_expr hftsoi/symbolfit/symbolfit/utils.py community (archive-listed) unverified MIT (permissive) · 83cf752c5fd1aa95 · report
square hftsoi/symbolfit/symbolfit/math_defs.py community (archive-listed) unverified MIT (permissive) · e4406709fbceb341 · report

Tasks

Interpretable Machine LearningSymbolic Regressionregression

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