AINeutralarXiv – CS AI · 7h ago6/10
🧠
From Uniform to Learned Graph Priors: Diffusion for Structure Discovery
Researchers propose Diff-prior, a diffusion-based adaptive prior system that improves neural relational inference (NRI) methods for discovering interaction graphs from data. Rather than relying on oversimplified uniform priors that treat edges independently, the new approach uses learned denoising-style calibration to produce more reliable and decisive structural discoveries across multiple NRI architectures.