add tutorials/examples on Equivariant GNNs

[CarloLucibello]

From @rbSparky comment #412 (comment)

After further discussion(on Slack), since it has been decided that it would be more valuable to implement more relevant applications, this discussion thread can now be used for writing the tutorial for "Molecular Property Prediction using EGNNs". It can serve as a part 2 to the current published tutorial, adding a regression task(using QM9) since currently only classification is shown
Paper
Dataset to be used: QM9
The above techniques from DropMessage can be incorporated as data augmentation technique (to show the user how to write custom functions for tasks like these)
This tutorial is in progress!

[ParamThakkar123]

@CarloLucibello I am Param Thakkar, currently pursuing my Bachelor of Technology in Computer Engineering at Veermata Jijabai Technological Institute, Mumbai.

I went through the projects for GSOC 2025 by Julialang and found the Graph Neural Networks projects very interesting. I would love to contribute to the project with my skill set under GSOC 2025 or JSOC 2025. Talking about my skill set I have worked a lot with Julia and I am proficient with it.

I am currently learning about graph neural networks from CS224W GNN course by Stanford's Jure Leskovec. I have also contributed to OrdinaryDiffEq.jl, SciMLBenchmarks.jl, Turing.jl, NeuralPDE.jl under the guidance and supervision of Prof. Christopher Rackauckas.

I am reaching out to seek your guidance on how I can contribute my best to your projects under your supervision in GSOC 2025.

[ParamThakkar123]

I even reached out to you via mail. I have gone through two projects. I am open to working on anyone of them