.. _citing:

Citing bayesn-td
==================

If you use bayesn-td in your research, please cite:

- Mandel et al. 2022 (MNRAS 510, 3, 3939-3966) — the BayeSN model
- Grayling et al. 2024 (`arXiv:2401.08755 <https://arxiv.org/abs/2401.08755>`_,
  MNRAS) — the BayeSN numpyro/JAX code that bayesn-td is built on
- Grayling et al. 2026 (`MNRAS 548 <https://doi.org/10.1093/mnras/stag340>`_)
  — the bayesn-td methodology paper

In addition, please cite the pre-trained BayeSN model you load:

- ``T21_model``: Thorp et al. 2021 (MNRAS 508, 3, 4310-4331)
- ``G26x_model``: Grayling et al. 2026 (MNRAS 548)
- ``M20_model``: Mandel et al. 2022 (MNRAS 510, 3, 3939-3966)
- ``W22_model``: Ward et al. 2023 (ApJ 956, 2, 111)

See :ref:`models` for full details of the available pre-trained models.