CITATION.cff

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "JAXSR: JAX-based Symbolic Regression"
abstract: "JAXSR is a fully open-source symbolic regression library built on JAX that discovers interpretable algebraic expressions from data. It uses sparse optimization techniques with JAX for automatic differentiation, JIT compilation, and GPU acceleration."
type: software
authors:
  - family-names: Kitchin
    given-names: John R.
    affiliation: Carnegie Mellon University
repository-code: "https://github.com/jkitchin/jaxsr"
url: "https://kitchingroup.cheme.cmu.edu/jaxsr/"
doi: 10.5281/zenodo.19542160
license: MIT
version: 0.3.0
keywords:
  - symbolic regression
  - JAX
  - machine learning
  - sparse optimization
  - model discovery
  - scientific computing
  - interpretable machine learning