This model is released under the Apache License 2.0.
@article{demarco2026stradavit,
title = {STRADAViT: Towards a Foundational Model for Radio Astronomy through Self-Supervised Transfer},
author = {DeMarco, Andrea and Fenech Conti, Ian and Camilleri, Hayley and Bushi, Ardiana and Riggi, Simone},
year = {2026},
note = {Under review},
archivePrefix = {arXiv},
primaryClass = {astro-ph.IM},
url = {
https://arxiv.org/abs/2603.29660v3}
}
This model was developed as part of the STRADA project on self-supervised transformers for radio astronomy.
If you build on this model, please acknowledge the project and cite the associated publication.
STRADAViT is intended as a domain-adapted starting point for radio astronomy imaging tasks.
It is suitable for:
STRADAViT is trained for transfer on radio astronomy imaging and should not be assumed to
outperform all off-the-shelf vision backbones in every downstream setting. In the current study:
HF-style classes for using STRADAViT can be found on
GitHub.
