cite PyG

Author: CarloLucibello

docs/src/tutorials/graph_classification_pluto.jl

@@ -25,6 +25,8 @@ using MLUtils
 md"""
 # Graph Classification with Graph Neural Networks
 
+*This Pluto noteboook is a julia adaptation of the Pytorch Geometric tutorials that can be found [here](https://pytorch-geometric.readthedocs.io/en/latest/notes/colabs.html).*
+
 In this tutorial session we will have a closer look at how to apply **Graph Neural Networks (GNNs) to the task of graph classification**.
 Graph classification refers to the problem of classifiying entire graphs (in contrast to nodes), given a **dataset of graphs**, based on some structural graph properties.
 Here, we want to embed entire graphs, and we want to embed those graphs in such a way so that they are linearly separable given a task at hand.