Geometric Network Comparisons
Abstract
Network analysis has a crucial need for tools to compare networks and assess the significance of differences between networks. We propose a principled statistical approach to network comparison that approximates networks as probability distributions on negatively curved manifolds. We outline the theory, as well as implement the approach on simulated networks.
Cite
Text
Asta and Shalizi. "Geometric Network Comparisons." Conference on Uncertainty in Artificial Intelligence, 2015.Markdown
[Asta and Shalizi. "Geometric Network Comparisons." Conference on Uncertainty in Artificial Intelligence, 2015.](https://mlanthology.org/uai/2015/asta2015uai-geometric/)BibTeX
@inproceedings{asta2015uai-geometric,
title = {{Geometric Network Comparisons}},
author = {Asta, Dena Marie and Shalizi, Cosma Rohilla},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2015},
pages = {102-110},
url = {https://mlanthology.org/uai/2015/asta2015uai-geometric/}
}