Latent geometry emerging from network-driven processes
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908683049369600 |
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| author | Beretta, Andrea Filippo Zanchetta, Davide Bontorin, Sebastiano De Domenico, Manlio |
| author_facet | Beretta, Andrea Filippo Zanchetta, Davide Bontorin, Sebastiano De Domenico, Manlio |
| contents | Understanding network functionality requires integrating structure and dynamics, and emergent latent geometry induced by network-driven processes captures the low-dimensional spaces governing this interplay. Here, we focus on generative-model-based approaches, distinguishing two reconstruction classes: fixed-time methods, which infer geometry at specific temporal scales (e.g., equilibrium), and multi-scale methods, which integrate dynamics across near- and far-from-equilibrium scales. Over the past decade, these models have revealed functional organization in biological, social, and technological networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_09616 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Latent geometry emerging from network-driven processes Beretta, Andrea Filippo Zanchetta, Davide Bontorin, Sebastiano De Domenico, Manlio Physics and Society Disordered Systems and Neural Networks Understanding network functionality requires integrating structure and dynamics, and emergent latent geometry induced by network-driven processes captures the low-dimensional spaces governing this interplay. Here, we focus on generative-model-based approaches, distinguishing two reconstruction classes: fixed-time methods, which infer geometry at specific temporal scales (e.g., equilibrium), and multi-scale methods, which integrate dynamics across near- and far-from-equilibrium scales. Over the past decade, these models have revealed functional organization in biological, social, and technological networks. |
| title | Latent geometry emerging from network-driven processes |
| topic | Physics and Society Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2506.09616 |