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.
Project description
dress-graph (Python)
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.
Install
pip install dress-graph
Quick start
from dress import fit
result = fit(
n_vertices=4,
sources=[0, 1, 2, 0],
targets=[1, 2, 3, 3],
)
print(result.edge_dress) # DRESS value for each edge
For the full API and documentation, see the main repository.
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