Symmetry-driven embedding of networks in hyperbolic space
Abstract Hyperbolic models are known to produce networks with properties observed empirically in most network datasets, including heavy-tailed degree distribution, high clustering, and hierarchical structures. As a result, several embedding algorithms have been proposed to invert these models and as...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-02122-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|