Update GitHub links

README.md

@@ -12,6 +12,8 @@ In this repository, we provide the pretrained models as described in our paper:
 
 Paper is available as pre-print via Arxiv: **[arXiv preprint arXiv:XXXX.XXXXX](https://arxiv.com)**
 
+This repository accompanies our [GitHub repository](GitHub repository https://github.com/freekholvoet/MultiviewSpatialEmbeddings) where you can find the code to train the models, as well as an exmaple on usage.
+
 ## Using the pretrained models
 
 The pretrained models, as described in Section 3.4 of the paper, are provided in this repository.
@@ -57,7 +59,7 @@ with torch.no_grad():
     emb = model(c.to(device).double()).detach().cpu().numpy()
 ```
 
-Replace `MODEL_NAME.ckpt` with the desired model filename from the list above. The Jupyter Notebook Add_embeddings_to_data.ipynb contains a function to systematically add embeddings to a data set containing a latitude and a longitude feature. 
+Replace `MODEL_NAME.ckpt` with the desired model filename from the list above. The [GitHub repository](GitHub repository https://github.com/freekholvoet/MultiviewSpatialEmbeddings) contains a Jupyter Notebook, called Add_embeddings_to_data.ipynb, that includes a function to systematically add embeddings to a data set containing a latitude and a longitude feature. 
 
 ## Citation