Xiuyuan Cheng

Preprint · October 2, 2024 Posterior sampling in high-dimensional spaces using generative models holds significant promise for various applications, including but not limited to inverse problems and guided generation tasks. Despite many recent developments, generating diverse poster ... Link to item Cite

Convergence of flow-based generative models via proximal gradient descent in Wasserstein space

Preprint · October 26, 2023 Flow-based generative models enjoy certain advantages in computing the data generation and the likelihood, and have recently shown competitive empirical performance. Compared to the accumulating theoretical studies on related score-based diffusion models, ... Link to item Cite

Xiuyuan Cheng

Scholarly Works - Preprints

Convergence Analysis and Acceleration of Fictitious Play for General Mean-Field Games via the Best Response

Posterior sampling via Langevin dynamics based on generative priors

Convergence of flow-based generative models via proximal gradient descent in Wasserstein space

The G-Invariant Graph Laplacian Part Ii: Diffusion Maps

The G-Invariant Graph Laplacian

Neural differential Recurrent Neural Network with adaptive time steps