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#machine learning Preprint Sep 2026

From Graphs to Feeders: Constraint-Guided Diffusion for Rule-Compliant Feeder Generation

The proposed PG-DiGress model injects feeder constraints into the reverse diffusion process through soft masks that suppress incompatible edge classes during denoising, followed by a final projection step that rebuilds a connected, rule-compliant feeder graph.

Yu-Yao Qin, Andrew Glaws, Aadil Latif et al. · 0 citations

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