Implementation of the paper:
End-to-End Learning of Probabilistic Hierarchies on Graphs
by Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann.
Published at ICLR'22.
Copyright (C) 2022
Daniel Zügner
Technical University of Munich
The fastest way to try our code is to use the Jupyter notebook notebooks/demo.ipynb.
In order to reproduce our results, refer to notebooks/experiments.ipynb as well as the hyperparameter configurations in configs/.
conda create -f env.yml
pip install -e .conda create -f env.cpu.yml
pip install -e .Please contact [email protected] in case you have any questions.
In the data folder we provide the following datasets originally published by
McCallum, Andrew Kachites, Nigam, Kamal, Rennie, Jason, and Seymore, Kristie.
Automating the construction of internet portals with machine learning.
Information Retrieval, 3(2):127–163, 2000.
and the graph was extracted by
Bojchevski, Aleksandar, and Stephan Günnemann. "Deep gaussian embedding of
attributed graphs: Unsupervised inductive learning via ranking." ICLR 2018.
Sen, Prithviraj, Namata, Galileo, Bilgic, Mustafa, Getoor, Lise, Galligher, Brian, and Eliassi-Rad, Tina.
Collective classification in network data.
AI magazine, 29(3):93, 2008.
Sen, Prithviraj, Namata, Galileo, Bilgic, Mustafa, Getoor, Lise, Galligher, Brian, and Eliassi-Rad, Tina.
Collective classification in network data.
AI magazine, 29(3):93, 2008.
Adamic, Lada A., and Natalie Glance. The political blogosphere and the 2004 US election: divided they blog. Proceedings of the 3rd international workshop on Link discovery. 2005.
Amunts, Katrin, et al. BigBrain: an ultrahigh-resolution 3D human brain model. Science 340.6139 (2013): 1472-1475.
Cho, Ara, et al. WormNet v3: a network-assisted hypothesis-generating server for Caenorhabditis elegans. Nucleic acids research 42.W1 (2014): W76-W82.
Aspert, Nicolas, et al. A graph-structured dataset for Wikipedia research. Companion Proceedings of The 2019 World Wide Web Conference. 2019.
Jani Patokallio. Openflight. online https://openflights.org.
Hu, Weihua, et al. Open graph benchmark: Datasets for machine learning on graphs. Advances in neural information processing systems 33 (2020): 22118-22133.
Yang, Jaewon, and Jure Leskovec. Defining and evaluating network communities based on ground-truth. Knowledge and Information Systems 42.1 (2015): 181-213.
Please cite our paper if you use the model or this code in your own work:
@inproceedings{
zugner2022endtoend,
title={End-to-End Learning of Probabilistic Hierarchies on Graphs},
author={Daniel Z{\"u}gner and Bertrand Charpentier and Morgane Ayle and Sascha Geringer and Stephan G{\"u}nnemann},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=g2LCQwG7Of}
}