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utils.py 2025-06-04 4.4 kB
sim_loss.py 2025-06-04 1.8 kB
sim_model.py 2025-06-04 3.0 kB
batch_sampler.py 2025-06-04 6.9 kB
clustering_metrics.py 2025-06-04 3.5 kB
clustering_module.py 2025-06-04 2.9 kB
plot_clusters.py 2025-06-04 967 Bytes
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Graph Clustering via Similarity-Aware Embeddings (GCSAE)

Deep graph clustering via RBF-Optimized embeddings with self-supervised learning

Requirements

[!NOTE] Higher versions should be also compatible.

  • torch
  • torchvision
  • torchaudio
  • torch-scatter
  • torch-sparse
  • torch-cluster
  • munkres
  • kmeans-pytorch
  • Scipy
  • Scikit-learn
pip install -r requirements.txt

Model

framework

Reproduction

The same code can be used for Citeseer, Amazon-Photo and Amazon-Computers by changing the dataset name.

  • Cora !python train.py --runs 1 --dataset 'Computers' --hidden '512' --1_1 100 --l_2 --tau 0.5 --ns 0.5 --lr 0.0005 --epochs_sim 150 --epochs_cluster 150 --wd 1e-3 --alpha 0.9
Source: README.md, updated 2025-06-04