FastParam Resource Hub

Welcome to the FastParam Resource Hub. Here you’ll find EPTA data, source code, and publications produced by the project. Each release aims to be FAIR—findable, accessible, interoperable, and reusable—so you can reproduce results, benchmark your own methods, and build on this work responsibly.

At a glance: browse the index on the left or scroll down to render any section.

Source Code

Heads up: FAIR artefacts are being published in stages. Items marked "Coming soon" will appear in the next updates; "External" links point to project-controlled sources (e.g., GitHub or a data catalogue) when appropriate. Following, you can visit the EPTA site where you can download the relevant data and source code, all the things for running your own experiments. They are under CC BY 4.0 and MIT Licence.

FastParam Core Repository

  • Languages: Python (PyTorch), JAX (planned)
  • Licence: MIT (TBC)
  • Visibility: Private (opening soon)

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Publications

This section lists journal & conference submissions, technical diagrams/notes, and selected

Journal & Conference Submissions

  • Addressing prior dependence in hierarchical Bayesian modeling for PTA data analysis I: Methodology and implementation
    • Status: In review
    • Type: Journal article
    Show short note
    Scope: NF-based hierarchical Bayesian inference for PTA analysis; improved statistical robustness & computational efficiency.
  • Addressing prior dependence in hierarchical Bayesian modeling for PTA data analysis II: Noise and SGWB inference through parameter decorrelation
    • Status: In review
    • Type: Journal article
    Show short note
    Scope: Application to pulsar noise modeling and SGWB detection using decorrelated hierarchical parameters.

Diagrams & Technical Notes

Licence & Citation

To support ethical reuse and proper attribution, FastParam provides default licensing and citation templates for datasets and software. Important: if a dataset or repository includes its own LICENSE, citation.txt, or DOI, that local file overrides the defaults below. Always prefer the per-item files when present.

If you adapt the datasets or code, indicate changes and, where practical, link back to this hub so others can find the original materials.

Software — Licence & how to cite

Licence (intended): MIT Licence (to be confirmed in the repository). A copy of the licence will be included as LICENSE in the repo. About MIT.

Recommended software citation (plain text)

FastParam Project (2025). FastParam Core (v0.1) — Generative models and characterisation tools.
Source code. URL: https://fastparam.koexai.com/resources/  Licence: MIT.

Software BibTeX (template)

@software{fastparam_core_v0_1_2025,
      author  = {FastParam Project},
      title   = {FastPara Core},
      year    = {2025},
      version = {0.1},
      url     = {https://fastparam.koexai.com/resources/},
      license = {MIT},
      note    = {Replace with repository URL and tag when public}
    }