Update README.md

README.md

@@ -103,6 +103,7 @@ Users are expected to:
 1. Load `cube` from this dataset as the clean target.
 2. Apply the forward model to obtain noisy / low-res inputs for denoising and super-resolution experiments.
 
+If you want to replicate our **exact** results, you can use the reference cube provided at `SampleCube/gt2.npz`.
 
 ## Usage
 ```python
@@ -165,6 +166,23 @@ loss.backward()
   year={2024},
   publisher={IEEE}
 }
+
+@article{ramirez2025super,
+  title={Super-Resolved 3D Satellite Lidar Imaging of Earth Via Generative Diffusion Models},
+  author={Ramirez-Jaime, Andres and Porras-Diaz, Nestor and Arce, Gonzalo R and Stephen, Mark},
+  journal={IEEE Transactions on Geoscience and Remote Sensing},
+  year={2025},
+  publisher={IEEE}
+}
+
+@inproceedings{ramirez2025denoising,
+  title={Denoising and Super-Resolution of Satellite Lidars Using Diffusion Generative Models},
+  author={Ramirez-Jaime, Andres and Porras-Diaz, Nestor and Arce, Gonzalo R and Stephen, Mark},
+  booktitle={2025 IEEE Statistical Signal Processing Workshop (SSP)},
+  pages={1--5},
+  year={2025},
+  organization={IEEE}
+}
 ```
 
 ## Maintainers