# Learning-Pytorch-Geometric

**Repository Path**: milo7hao/Learning-Pytorch-Geometric

## Basic Information

- **Project Name**: Learning-Pytorch-Geometric
- **Description**: This repository is mainly a collection of some simple examples of learning PyG, with detailed procedures, from data loading, to model building, to training, forecasting, and visualization. It can be run directly in Google Colab.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-10
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Learning-Pytorch-Geometric

## Introduction

This repository is mainly a collection of some simple examples of learning PyG, with detailed procedures, from data loading, to model building, to training, forecasting, and visualization. 

And other demo about ML, such as PCA 

**It can be run directly in Google Colab.**



## Main Content

- [x] [Visualization of graph data](Networkx_Draw_Graph/Networkx_Draw_Graph.ipynb)

- [x] [Spectral clustering](Graph_Serctral_Clustering/Graph_Serctral_Clustering.ipynb)

  ![spectral_clustering_result](Graph_Serctral_Clustering/spectral_clustering_result.png)

- [x] [Graph Convolution for Semi-supervised Clustering of Karate Datasets](GCN_Demo/GCN_Demo.ipynb) From [[Semi-Supervised Classification with Graph Convolutional Networks](https://arxiv.org/abs/1609.02907) (ICLR 2017)]

  ![result](GCN_Demo/result.gif)

- [x] [SAGE_Conv](SAGE_Conv\SAGE_Conv.ipynb) 

- [x]  [pytorch_geometric_Message_Passing_test](PyG_test\pytorch_geometric_Message_Passing_test.ipynb) 

- [ ] PointNet