Critique 0

Very nicely written and well explained. I personally liked the mention of the limitations - "Problems with Graph Neural Networks". I have some minor suggestions:

Maybe you can elaborate a bit more on the adjacency list, where you use the same example that you used for the adjacency matrix also to describe adjacency list and how it differs from the matrix.

It was a bit unclear: "There are broadly three kinds of tasks on graphs,"

You can also explain the figure of Zach's Karate Club with a small text description. I found it a bit difficult to connect the image with the text on node-level prediction.

It was slightly confusing: "*Note: A pooling layer is generally present if we need a graph-level representation/embedding. This is useful when we want to do graph-level tasks." In what cases is the pooling layer not available?

I like the discussion on permutation invariance and equivariance. I think it is a very important property of GNNs.

Can you also give one-line simplified motivation/intuition behind GCN and Graph attention Networks?

Thank you so much for the review. I have made changes accordingly.

> Maybe you can elaborate a bit more on the adjacency list, where you use the same example that you used for the adjacency matrix also to describe adjacency list and how it differs from the matrix.

Added a short explanation on how it would look like.

> It was a bit unclear: "There are broadly three kinds of tasks on graphs,"

Changed this.

> You can also explain the figure of Zach's Karate Club with a small text description. I found it a bit difficult to connect the image with the text on node-level prediction.

It was initially in the node classification description. Moved it to the image caption.

> It was slightly confusing: "*Note: A pooling layer is generally present if we need a graph-level representation/embedding. This is useful when we want to do graph-level tasks." In what cases is the pooling layer not available?

I just removed it. I think the complication wasn't needed.