Data

Tools

Indexes

Applications

Experiments

Open Source Science

pytorchgeometric

https://github.com/mesfind/pytorchgeometric

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (4.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: mesfind
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 17 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 4 years ago · Last pushed over 4 years ago
Metadata Files
Readme Citation

README.md

Pytorch Geometric

This is 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 library, an extension to Pytorch to deal with graphs and structured data, developed by @rusty1s.

Tutorials:

  • Tutorial1: What is Geometric Deep Learning Open In Colab

  • Tutorial2: PyTorch basics.- Open In Colab

  • Tutorial3: Graph Attention Network GAT. - Open In Colab

  • Tutorial4: Convolutional Layers - Spectral methods. - Open In Colab

  • Tutorial5: Aggregation Functions in GNNs. - Open In Colab

  • Tutorial6: Graph Autoencoders and Variational Graph Autoencoders. - Open In Colab

  • Tutorial7: Adversarially regularized GAE and VGAE - Open In Colab

  • Tutorial8: Graph Generation.

  • Tutorial9: Recurrent Graph Neural Networks. - Open In Colab Open In Colab

  • Tutorial10: DeepWalk and Node2Vec (Theory).

  • Tutorial11: DeepWalk and Node2Vec (Practice). - Open In Colab

  • Tutorial12: Edge analysis. - Open In Colab Open In Colab

  • Tutorial13: Metapath2vec. - Open In Colab

  • Tutorial14: Data handling in Pyg (part 1)] - Open In Colab

  • Tutorial15: [Data handling in Pyg (part 2)] - Open In Colab

  • Tutorial16: Graph pooling: DIFFPOOL. - Open In Colab

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 to find suitable versions.

Owner

  • Name: Mesfin Diro
  • Login: mesfind
  • Kind: user
  • Location: Addis Ababa, Ethiopia
  • Company: @ET-AI

Computational Data Scientist. Executive Council member for @carpentries. Trainer & Instructor for @carpentries

Citation (CITATION.cff) 

message: "If you use this software, please cite it as below."
authors:
  - family-names: Longa
    given-names: Antonio
    orcid: https://orcid.org/0000-0003-0337-1838
  - family-names: Pellegrini
    given-names: Giovanni
    orcid: hhttps://orcid.org/0000-0003-2848-8338
  - family-names: Santin
    given-names: Gabriele
    orcid: https://orcid.org/0000-0001-6959-1070

title: "PytorchGeometricTutorial"
version: 1.0.0
date-released: 2021-10-23
url: "https://github.com/AntonioLonga/PytorchGeometricTutorial"

GitHub Events

Total
Last Year