Update README.md

README.md

@@ -122,12 +122,11 @@ Training scripts available in the [BDAPPV dataset repository](https://huggingfac
 If you use these models, please cite:
 
 ```bibtex
-@phdthesis{kasmi2024enhancing,
-  title  = {Enhancing the Reliability of Deep Learning Models to Improve
-            the Observability of French Rooftop Photovoltaic Installations},
-  author = {Kasmi, Gabriel},
-  year   = {2024},
-  school = {Universit{\'e} Paris sciences et lettres}
+@article{kasmi2022towards,
+  title={Towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed PV mapping},
+  author={Kasmi, Gabriel and Dubus, Laurent and Blanc, Philippe and Saint-Drenan, Yves-Marie},
+  journal={arXiv preprint arXiv:2207.07466},
+  year={2022}
 }
 ```
 
@@ -135,4 +134,4 @@ If you use these models, please cite:
 
 - Mayer et al. (2022). [3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D.](https://doi.org/10.1016/j.apenergy.2021.118469) *Applied Energy*, 310, 118469. *(source of the base checkpoints)*
 - Kasmi et al. (2023). [A crowdsourced dataset of aerial images with annotated solar photovoltaic arrays and installation metadata.](https://doi.org/10.1038/s41597-023-01951-4) *Scientific Data*, 10, 59. *(BDAPPV dataset)*
-- Kasmi et al. (2022). [Towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed PV mapping.](https://arxiv.org/abs/2207.07466) *arXiv:2207.07466*. *(cross-provider distribution shift)*
+- Kasmi et al. (2025). [Space-scale exploration of the poor reliability of deep learning models: the case of the remote sensing of rooftop photovoltaic systems.](https://doi.org/10.1017/eds.2025.13) *Environmental Data Science*. *(cross-provider distribution shift)*