3 papers
stat.ML2026
Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds
Yizhu Wang, Mu Niu, Xiaochen Yang
We introduce the Intrinsic Hybrid Latent Diffusion Model (ILDM), a generative framework that integrates probabilistic dimensionality reduction with geometry-aware diffusion on unkn…
eess.IV2026
MAP-based Problem-Agnostic diffusion model for Inverse Problems
Pingping Tao, Haixia Liu, Jing Su
Diffusion models have indeed shown great promise in solving inverse problems in image processing. In this paper, we propose a novel, problem-agnostic diffusion model called the max…
stat.ML2025
Atlas Gaussian processes on restricted domains and point clouds
Mu Niu, Yue Zhang, Ke Ye +3
In real-world applications, data often reside in restricted domains with unknown boundaries, or as high-dimensional point clouds lying on a lower-dimensional, nontrivial, unknown m…