21 citations · 49 across the 12 of their papers we have counts for
14 papers
Denoising Data with Measurement Error Using a Reproducing Kernel-based Diffusion Model
Mingyang Yi, Marcos Matabuena, Zhiming Ma +1
The ongoing technological revolution in measurement systems enables the acquisition of high-resolution samples in fields such as engineering, biology, and medicine. However, these…
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space
Mingyang Yi, Bohan Wang
Recently, optimization on the Riemannian manifold have provided valuable insights to the optimization community. In this regard, extending these methods to to the Wasserstein space…
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
Shuchen Xue, Mingyang Yi, Weijian Luo +4
Diffusion Probabilistic Models (DPMs) have achieved considerable success in generation tasks. As sampling from DPMs is equivalent to solving diffusion SDE or ODE which is time-cons…
On the Generalization of Diffusion Model
Mingyang Yi, Jiacheng Sun, Zhenguo Li
The diffusion probabilistic generative models are widely used to generate high-quality data. Though they can synthetic data that does not exist in the training set, the rationale b…
Breaking Correlation Shift via Conditional Invariant Regularizer
Mingyang Yi, Ruoyu Wang, Jiachen Sun +2
Recently, generalization on out-of-distribution (OOD) data with correlation shift has attracted great attentions. The correlation shift is caused by the spurious attributes that co…
Out-of-distribution Generalization with Causal Invariant Transformations
Ruoyu Wang, Mingyang Yi, Zhitang Chen +1
In real-world applications, it is important and desirable to learn a model that performs well on out-of-distribution (OOD) data. Recently, causality has become a powerful tool to t…