Scale-invariant graph embeddings whose parameters add under node merging give consistent multi-scale network reconstructions, with accuracy that depends on the metric and model family.
As a result, the fitnCM is expected to yield better local-level predictions compared to the MSMs (refer to 7a)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.soc-ph 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Renormalizable Graph Embeddings For Multi-Scale Network Reconstruction
Scale-invariant graph embeddings whose parameters add under node merging give consistent multi-scale network reconstructions, with accuracy that depends on the metric and model family.