.zenodo.json

{
  "title": "JAXSR: JAX-based Symbolic Regression",
  "description": "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.",
  "upload_type": "software",
  "access_right": "open",
  "license": "MIT",
  "creators": [
    {
      "name": "Kitchin, John R.",
      "affiliation": "Carnegie Mellon University"
    }
  ],
  "keywords": [
    "symbolic regression",
    "JAX",
    "machine learning",
    "sparse optimization",
    "model discovery",
    "scientific computing",
    "interpretable machine learning"
  ],
  "related_identifiers": [
    {
      "identifier": "https://github.com/jkitchin/jaxsr",
      "relation": "isSupplementTo",
      "scheme": "url"
    }
  ]
}