dress.graph: DRESS - A Continuous Framework for Structural Graph Refinement
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, guaranteed
bitwise-equal across any vertex labeling, 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.
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