SRG

This is a pytorch implementation of the paper: Super Resolution Graph with Conditional Normalizing Flows for Temporal Link Prediction. The baselines used in the paper will be released as a toolbox soon.

Requirements

torch (1.10.1)

numpy (1.21.6)

Prepare the data

unzip the data.zip into ./data;

for other dataset, use ./generate_data/preprocess_LR.py to split the original data, and the settings including node_num are setted in the ./generate_data/baseconfig.yml.

Run

python run.py