dress-graph

DRESS is a deterministic, parameter-free framework that iteratively refines the structural similarity of edges in a graph to produce a canonical fingerprint: a real-valued edge vector, obtained by converging a non-linear dynamical system to its unique fixed point. The fingerprint is isomorphism-invariant by construction, numerically stable (no overflow, no error amplification, no undefined behavior), fast and embarrassingly parallel to compute: DRESS total runtime is O(I * m * d_max) for I iterations to convergence, and convergence is guaranteed by Birkhoff contraction.