This repository contains two main experiments:

In this study, we use the KGEMs reimplemented in PyKEEN and the authors' best reported hyperparameters to make reproductions of past experiments.

In this study, we conduct a large number of hyper-parameter optimizations to investigate the effects of certain aspects of models (training assumption, loss function, regularizer, optimizer, negative sampling strategy, HPO methodology, training strategy). There are two folders:

1. config - The ablation study configuration JSON files used in the experiments
2. results - The results from the ablation studies based on the configuration files

A summary of the results can be found here

git clone https://github.com/mali-git/pykeen_experimental_results.git cd pykeen_experimental_results pip install -e . # ABLATION python ablation/collate.py python ablation/paper_plots.py python ablation/plot.py # REPRODUCTIONS python reproducibility/generate_summary_table.py python reproducibility/plot.py