Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"

Last update: Oct 12, 2022

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Overview

DPGNN

This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"

Requirements

PyTorch 1.8.1+cu111
PyTorch Geometric 1.7.0
Pytorch-scatter 2.0.7
NetworkX 2.5.1
Tqdm 4.61.0
Sklearn 0.0

Note that the version of PyTorch and PyTorch Geometric should be compatible and PyTorch Geometric is related to other packages, which requires to be installed beforehand. It is recommended to follow the installation instruction.

Run

To reproduce the performance comparison and the ablation study in the following Table and the Figure , run

bash run.sh

To reproduce our results under different imbalance ratio, run

bash run_ratio.sh

Owner

Yu Wang (Jack)

A 1st year Ph.D. student in the Computer Science Department at Vanderbilt University. Research work: graph data mining, deep learning, network analysis

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