Add pipeline tag and license, update primary paper link

This PR enhances the model card by:

* Adding the `pipeline_tag: image-to-image` to the metadata, making the model discoverable in the relevant category on the Hugging Face Hub, as its functionality directly relates to image restoration.
* Adding the `license: apache-2.0` to the metadata for clarity regarding usage rights.
* Updating the link for the paper "Deep priors for satellite image restoration with accurate uncertainties" to its Hugging Face Papers page: `https://huggingface.co/papers/2412.04130`.

These changes improve the discoverability and clarity of the model's information.

README.md

@@ -1,22 +1,24 @@
 ---
-tags:
-- compression
-- compressAI
-- VAE
 datasets:
 - FFHQ256
 - Satellite_PCRS
 - BSDS500
 - CelebA
-library_name: "PyTorch"
-
+library_name: PyTorch
+tags:
+- compression
+- compressAI
+- VAE
+pipeline_tag: image-to-image
+license: apache-2.0
 ---
+
 # Description of available models
 
 The models are variational autoencoders (VAEs) and compressive autoencoders (CAEs), with an additional variance decoder, that can be used for restoring images using 
 Variational Bayes Latent Estimation (VBLE) algorithm.
 - **Associated GitHub Repository:** [Github Repo](https://github.com/MaudBqrd/VBLExz)
-- **Associated Papers:** [Deep Priors for satellite image restoration with accurate uncertainties](https://ieeexplore.ieee.org/abstract/document/11258607),
+- **Associated Papers:** [Deep Priors for satellite image restoration with accurate uncertainties](https://huggingface.co/papers/2412.04130),
 [Variational Bayes image restoration with compressive autoencoders](https://ieeexplore.ieee.org/abstract/document/10982450)
 
 ## Models Details
@@ -79,13 +81,13 @@ and a realistic satellite dataset simulated from PCRS [5].
 - Dataset: FFHQ256 (RGB)
 - Bitrate parameter ```alpha = 0.1800``` (high bitrate model)
 
-<ins>mbt_25cm_PCRS_0.3600_std-diagonal</ins>
-- Architecture: mbt [1] model with latent dimension ```M = 320```
+<ins>mbt_25cm_PCRS_0.3600_std-diagonal</ins>:
+- Architecture: mbt [1] model with latent dimension ```M = 320```.
 - Dataset: PCRS (satellite images downsampled at 25cm resolution, white and black)
 - Bitrate parameter ```alpha = 0.3600``` (very high bitrate model)
 
-<ins>mbt_50cm_PCRS_0.3600_std-diagonal</ins>
-- Architecture: mbt [1] model with latent dimension ```M = 320```
+<ins>mbt_50cm_PCRS_0.3600_std-diagonal</ins>:
+- Architecture: mbt [1] model with latent dimension ```M = 320```.
 - Dataset: PCRS (satellite images downsampled at 50cm resolution, white and black)
 - Bitrate parameter ```alpha = 0.3600``` (very high bitrate model)
 
@@ -183,4 +185,4 @@ Contact: maud.biquard@laposte.net
 
 [4] Martin, D., Fowlkes, C., Tal, D., & Malik, J. (2001, July). A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In Proceedings eighth IEEE international conference on computer vision. ICCV 2001 (Vol. 2, pp. 416-423). IEEE.
 
-[5] Institut Géographique National (IGN), [https://www.data.gouv.fr/datasets/pcrs/]
+[5] Institut Géographique National (IGN), [https://www.data.gouv.fr/datasets/pcrs/]