A Continuous Framework for Structural Graph Refinement
DRESS is a deterministic, parameter-free framework for continuous structural graph refinement. It iterates a nonlinear dynamical system on real-valued edge similarities and produces a graph fingerprint as a sorted edge-value vector once the iteration reaches a prescribed stopping criterion. The resulting fingerprint is self-contained, isomorphism-invariant by construction, reproducible across vertex labelings under the reference implementation, numerically robust in practice, and efficient to compute with straightforward parallelization and distribution.
using DRESS
result = fit(4, [0, 1, 2, 0], [1, 2, 3, 3])
println(result.edge_dress)For the full API and documentation, see the main repository.