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Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature
Describing networks geometrically through low-dimensional latent metric spaces has helped design efficient learning algorithms, unveil network symmetries and study dynamical network processes. However, latent space embeddings are limited to specific classes of networks because incompatible metric sp...
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| Published in: | Nat Commun |
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| Main Authors: | , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
Nature Publishing Group UK
2021
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8316456/ https://ncbi.nlm.nih.gov/pubmed/34315911 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-021-24884-1 |
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