# PytorchGeometricTutorial

**Repository Path**: leomk2004/PytorchGeometricTutorial

## Basic Information

- **Project Name**: PytorchGeometricTutorial
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-09-11
- **Last Updated**: 2024-09-11

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# PytorchGeometricTutorial
Hi! We are Antonio Longa and Giovanni Pellegrini, PhD students, and Gabriele Santin, researcher, working between Fondazione Bruno Kessler and the University of Trento, Italy.

This project aims to present through a series of tutorials various techniques in the field of Geometric Deep
Learning, focusing on how they work and how to implement them using the [Pytorch geometric](https://github.com/rusty1s/pytorch_geometric)
library, an extension to Pytorch to deal with graphs and structured data,
developed by [@rusty1s](https://github.com/rusty1s).

You can find our video tutorials on [Youtube](https://www.youtube.com/user/94longa2112/featured) and at our official website [here.](https://antoniolonga.github.io/Pytorch_geometric_tutorials/index.html)

Feel free to join our weekly online tutorial! For more details, have a look at the  [official website.](https://antoniolonga.github.io/Pytorch_geometric_tutorials/index.html)

### Tutorials:

* Tutorial1: [What is Geometric Deep Learning?](https://youtu.be/JtDgmmQ60x8) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial1/Tutorial1.ipynb)

* Tutorial2: [PyTorch basics.](https://youtu.be/UHrhp2l_knU) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial2/Tutorial2.ipynb)

* Tutorial3: [Graph Attention Network GAT.](https://youtu.be/CwsPoa7z2c8) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial3/Tutorial3.ipynb)

* Tutorial4: [Convolutional Layers - Spectral methods.](https://youtu.be/Ghw-fp_2HFM) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial4/Tutorial4.ipynb)

* Tutorial5: [Aggregation Functions in GNNs.](https://youtu.be/tGXovxQ7hKU) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial5/Aggregation%20Tutorial.ipynb)

* Tutorial6: [Graph Autoencoders and Variational Graph Autoencoders.](https://youtu.be/qA6U4nIK62E) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial6/Tutorial6.ipynb)

* Tutorial7: [Adversarially regularized GAE and VGAE.](https://youtu.be/hZkLu2OaHD0) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial7/Tutorial7.ipynb)

* Tutorial8: [Graph Generation.](https://youtu.be/embpBq1gHAE)

* Tutorial9: [Recurrent Graph Neural Networks.](https://youtu.be/v7TQ2DUoaBY) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial9/Tutorial9.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial9/RecGNN_tutorial.ipynb)

* Tutorial10: [DeepWalk and Node2Vec (Theory).](https://youtu.be/QZQBnl1QbCQ)

* Tutorial11: [DeepWalk and Node2Vec (Practice).](https://youtu.be/5YOcpI3dB7I) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial11/Tutorial11.ipynb)

* Tutorial12: [Edge analysis.](https://youtu.be/m1G7oS9hmwE) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial12/Tutorial12%20GAE%20for%20link%20prediction.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial12/Tutorial12%20Node2Vec%20for%20label%20prediction.ipynb)

* Tutorial13: [Metapath2vec.](https://youtu.be/GtPoGehuKYY) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial13/Tutorial13.ipynb)

* Tutorial14: [Data handling in Pyg (part 1)](https://youtu.be/Vz5bT8Xw6Dc) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial14/Tutorial14.ipynb)

* Tutorial15: [Data handling in Pyg (part 2)](https://youtu.be/Q5T-JdyVCfs) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial15/Tutorial15.ipynb)

* Tutorial16: [Special guest talk - Matthias Fey](https://youtu.be/MA6VH7Vwtb4)

* Tutorial17: [Special guest talk - Sergei Ivanov](https://youtu.be/hX297pr1RHE)

* Tutorial18: [Graph pooling: DIFFPOOL.](https://youtu.be/Uqc3O3-oXxM) - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial16/Tutorial16.ipynb)

### Installation of PyG:
In order to have running notebooks in Colab, we use the following installation commands:
```
!pip install torch-scatter -f https://data.pyg.org/whl/torch-1.9.0+cu111.html
!pip install torch-sparse -f https://data.pyg.org/whl/torch-1.9.0+cu111.html
!pip install torch-geometric
```
These version are tested and running in Colab. If instead you run the notebooks on your machine, have a look at the PyG's [installation instructions](https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html) to find suitable versions.