blog link added + blog tab moved

Author: RobertoNeglia

_config.yml

@@ -50,9 +50,9 @@ minima:
 header_pages:
   - people.html
   - publications.html
+  - blog.html
   - theses.md
   - news.md
-  - blog.html
 
 collections:
   events:

_posts/2025-10-03-welcome-to-our-blog.md

@@ -18,13 +18,11 @@ Alongside the formal presentation in our papers, we aim to complement it here wi
 
 Our work spans several exciting areas:
 
-TODO -> add links to papers where possible
-
 - 🎱 **Graph Pooling**: Techniques for down-sampling graph structures while preserving important information ([library](https://torch-geometric-pool.readthedocs.io/en/latest/), [AB25](https://arxiv.org/pdf/2409.05100?), [CB25](https://arxiv.org/abs/2501.09821), [GZB+22](https://arxiv.org/pdf/2110.05292));
-- 📊 **Spatiotemporal modeling**: Using graphs to model complex temporal dependencies ([HCB25](https://openreview.net/forum?id=MHQXfiXsr3), [MAB24](https://arxiv.org/pdf/2402.10634));
-- 🎯 **Uncertainty Quantification**: Assessing and mitigating uncertainty in forecasting in both structured and unstructured data domains ([CJM+25](https://arxiv.org/pdf/2502.09443), [GSB23](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10360823));
+- 📊 **Spatiotemporal modeling**: Using graphs to model complex temporal dependencies ([HCB25](https://openreview.net/forum?id=MHQXfiXsr3), [MAB24](https://arxiv.org/pdf/2402.10634), [CMB+23](https://ojs.aaai.org/index.php/AAAI/article/view/25880));
+- 🎯 **Uncertainty Quantification**: Assessing and mitigating uncertainty in forecasting in both structured and unstructured data domains ([NCB+25](https://arxiv.org/abs/2510.05060), [CJM+25](https://arxiv.org/pdf/2502.09443), [GSB23](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10360823));
 - 🔬 **Interpretability**: Making spatiotemporal models more transparent and trustworthy ([GSB24](https://arxiv.org/pdf/2410.13469), [GSS+23](https://arxiv.org/pdf/2209.07926));
-- ⚡ **Scalability**: Breaking barriers to handle massive real-world datasets ([CMB+23](https://ojs.aaai.org/index.php/AAAI/article/view/25880)).
+- ⚡ **Scalability**: Breaking barriers to handle massive real-world datasets ([NCB+25](https://arxiv.org/abs/2510.05060), [CMB+23](https://ojs.aaai.org/index.php/AAAI/article/view/25880)).
 
 ## What You'll Find Here
 
@@ -35,7 +33,6 @@ In this blog, we'll be sharing:
 - **Practical applications** of graph neural networks;
 - **Updates** on our group activities, collaborations and events.
 
-
 ---
 
 *Stay tuned for our upcoming posts, where we'll dive deep into our latest research.*