5 citations · 5 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Warped multifidelity Gaussian processes for data fusion of skewed environmental data
Pietro Colombo, Claire Miller, Xiaochen Yang +2
Understanding the dynamics of climate variables is paramount for numerous sectors, like energy and environmental monitoring. This study focuses on the critical need for a precise m…