Centrality Learning

This repository is intended to contain tools and methods for learning arbitrary centrality measures for arbitrary graphs.

Currently two methods are available:

• learned_routing_centrality (original code by Liav Bachar can be found here: https://github.com/liavbach/LRC )
• centrality_from_auralized_nodes
• learning_a_routing_centrality_based_on_graph_auralization(original code by Xin Li can be found here: https://github.com/bizhili/LRCGA)

Relevant publications:

@inproceedings{bachar2021learning,
  title={Learning Centrality by Learning to Route},
  author={Bachar, Liav and Elyashar, Aviad and Puzis, Rami},
  booktitle={International Conference on Complex Networks and Their Applications},
  pages={247--259},
  year={2021},
  organization={Springer}
}

@inproceedings{puzis2021can,
  title={Can one hear the position of nodes?},
  author={Puzis, Rami},
  booktitle={International Conference on Complex Networks and Their Applications},
  pages={to appear},
  year={2022},
}

@article{li2023centrality,
  title={Centrality Learning: Auralization and Route Fitting},
  author={Li, Xin and Bachar, Liav and Puzis, Rami},
  journal={Entropy},
  volume={25},
  number={8},
  pages={1115},
  year={2023},
  publisher={MDPI}
}