Dynamic networks can be modeled as decorated graphons whose edge labels are binary time-series laws, estimated by two-stage blockwise least squares with rates depending on the number of time steps and edge-estimator quality.
Title resolution pending
1 Pith paper cite this work, alongside 76 external citations. Polarity classification is still indexing.
1
Pith paper citing it
76
external citations · OpenAlex
fields
stat.ME 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Decorated graphons for temporal network estimation
Dynamic networks can be modeled as decorated graphons whose edge labels are binary time-series laws, estimated by two-stage blockwise least squares with rates depending on the number of time steps and edge-estimator quality.