AI RESEARCH
Kuramoto Orientation Diffusion Models
arXiv CS.LG
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ArXi:2509.15328v3 Announce Type: replace Orientation-rich images, such as fingerprints and textures, often exhibit coherent angular directional patterns that are challenging to model using standard generative approaches based on isotropic Euclidean diffusion. Motivated by the role of phase synchronization in biological systems, we propose a score-based generative model built on periodic domains by leveraging stochastic Kuramoto dynamics in the diffusion process.