AI RESEARCH

Mat\'ern Noise for Triangulation-Agnostic Flow Matching on Meshes

arXiv CS.LG

ArXi:2605.19305v1 Announce Type: cross This paper tackles the task of learning to generate signals over triangle meshes in a triangulation-agnostic manner, meaning the trained model can be applied to different meshes and triangulations effectively. Practically, the paper adapts the flow matching (FM) paradigm to a mesh-based, triangulation-agnostic setting. Theoretically, it proposes a specific noise distribution which is triangulation agnostic, to be used inside the FM model's denoising process.