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Constraint-Preserving Flow Matching for Spectral Graph Generation
Not provided in the abstract
graph generationspectral methodsmachine learningconstraint optimization
2611.05436
Builder Relevance
2h ago70%
Abstract
This paper introduces a method for generating spectral graphs while preserving essential structural properties of graph Laplacians.
Reality Card
Core Claim
The proposed Laplacian-Constrained Stiefel Flow Matching (LaSFM) method successfully preserves both the nullspace condition and eigenvector orthonormality during spectral graph generation.
Method / Result
LaSFM improves performance on spectral and graph-level metrics, aligning better with target properties.
Limitations
The abstract does not specify limitations or reproducibility concerns.
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