An $L^p$ theory of sparse graph convergence I: Limits, sparse random graph models, and power law distributions

Cited in riva2026intensity as the L^p extension of graphon theory that handles sparse graphs, contextualizing IDPG's own dense-to-sparse interpolation as an alternative route through Poisson lifetimes rather than L^p kernel relaxations.