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Pytorch implementaion of JK-Net, paper: Representation Learning on Graphs with Jumping Knowledge Networks

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JK-Net-Pytorch

Pytorch implementation of JK-Net, paper: Representation Learning on Graphs with Jumping Knowledge Networks. Supported datasets are cora and citeseer.

Referenced Repositories:

  1. Code of tensorflow implementation
  2. Pytorch implementation with dgl

Requirements

* PyTorch 1.14
* Python 3.7

Usage

python train.py --dataset dataset_name --model model_name --layer layer_name
--dataset_name: core, citseer
--model: Concat, Maxpooling, LSTM, GCN, GAT
--layer: GCN, GAT

Reference

Paper: Representation Learning on Graphs with Jumping Knowledge Networks

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Pytorch implementaion of JK-Net, paper: Representation Learning on Graphs with Jumping Knowledge Networks

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