2 papers
cs.CV2026
Be Tangential to Manifold: Discovering Riemannian Metric for Diffusion Models
Shinnosuke Saito, Takashi Matsubara
Diffusion models are powerful deep generative models, but unlike classical models, they lack an explicit low-dimensional latent space that parameterizes the data manifold. This abs…
cs.CV2025
Image Interpolation with Score-based Riemannian Metrics of Diffusion Models
Shinnosuke Saito, Takashi Matsubara
Diffusion models excel in content generation by implicitly learning the data manifold, yet they lack a practical method to leverage this manifold - unlike other deep generative mod…