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This is an official PyTorch implementation of paper "Interpretable Signed Link Prediction with Signed Infomax Hyperbolic Graph"

Contents

Requirements

python            3.7.3
texttable         1.5.0
tqdm              4.32.1
numpy             1.15.4
scikit-learn      0.1.2
scipy             1.3.0
sklearn           0.20.0
torch             1.4.0
torch-scatter     2.0.4
torch-sparse      0.6.1
torch-cluster     1.5.4
torch-geometric   1.5.0
torchvision       0.5.0
tensorboardX      1.8

Dataset Preparation

Put the edge source files in ./input

Usage

To run SIHG model with the default setting:

python src/main.py

Logs

We save the embedding and evaluation scores as scalar in ./src/logs

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official PyTorch implementation of paper "Interpretable Signed Link Prediction with Signed Infomax Hyperbolic Graph" (TKDE2021)

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