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Generative Regularities in Multi-Layer Networks: A Shared-Latent Space Representation Approach

Usages

Type: python support_main.py --dataset Aarhus to have a try of SupportNet on the Aarhus network.

Type: python support_main.py --dataset Aarhus --onlyTest to only load the model for prediction.

Type: python support_main.py --dataset Aarhus --epochs 100 --EarlyStop --patience 20 Use early stopping strategy. Set the maximum number of epochs for model training. Set the number of patient epochs for the early stop strategy.

Type: python support_main.py --dataset XXX --best_metric aupr --best_metric: Which metric should be chosen as the best model performance indicator: AUC, AP, AUPR, ...

Type: python support_main.py --dataset XXX --set_seed 42 --set_seed to set the random seed, 42 or 2025 or ...

Type: --gcn_type GCN --gcn_type JK_GCN Configure the GCN type used by the Layer-wise Representation Extractor in SupportNet: Currently, both GCN and JK_GCN are supported.

Type: --gcn_layer 4 Configure the number of layers in the Layer-wise Representation Extractor's GCN in SupportNet to aggregate information across multiple hops. e.g., 2, 3, 4.


Type: python CLGC_main.py --Eval_layers Aarhus_1 Aarhus_2 Evaluate the cross-layer generation consistency score (CLGC score) of Aarhus_1 and Aarhus_2.

Type: python CLGC_main.py --Eval_layers Aarhus_1 small_world Evaluate the cross-layer generation consistency score (CLGC score) of Aarhus_1 and the theoretical network small_world. Currently, three theoretical networks are supported: small_world, scale_free, and random_graph.

Type: python CLGC_main.py --Eval_layers Aarhus_1 Enron_1 Kapferer_1 LonRail_1 Evaluate the cross-layer generation consistency score (CLGC score) of the group: Aarhus_1 Enron_1 Kapferer_1 LonRail_1.

Type: python run.py can directly reproduce CLGC-related experiments.

Requirements

Latest tested combination: Python 3.8 + Pytorch 2.1

Package Version


imbalanced-learn 0.12.4 matplotlib 3.7.5 networkx 2.8.8 numpy 1.24.1 node2vec 0.4.6 pandas 2.0.3 scikit-learn 1.3.2 torch 2.1.0 torch-cluster 1.6.2+pt21cu121 torch_geometric 2.4.0 torch-scatter 2.1.2+pt21cu121 torch-sparse 0.6.18+pt21cu121 torch-spline-conv 1.2.2+pt21cu121 torchaudio 2.1.0 torchvision 0.16.0 tqdm 4.67.1

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