Code for Temporal Gaussian Network Embedding

Requirements

numpy==1.23.4
pandas==1.5.3
pyro_ppl==1.8.4
torch==1.12.1
tqdm==4.64.1
matplotlib==3.3.4
sacred==0.8.4

The sacred library is used in the training script to save the trained model in a run-specific folder, along with the config file and some metrics.

Example training

The training can be run on different datasets by running the following commands

To train on the highschool dataset, run

python train.py with config/highschool.yaml

To train on the toy dataset, run

python train.py with config/toy.yaml

Example analysis of the trained tgne models

In notebooks, we provide examples of how to visualize the 2d embeddings obtained through TGNE on the toy dataset and the highschool dataset.

For any questions, please contact Raphaël Romero at raphael.romero@ugent.be.