This repository contains implementation for paper "CLGNN: A Contrastive Learning-based GNN for Temporal Betweenness Prediction under Extreme Value Imbalance"

Code is written in Python and the proposed model is implemented using Pytorch.

Running the code: python -u main.py -d test-dataset --lr 0.01 The test datasets are available on http://snap.stanford.edu/data and https://graphdata.net.