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stat.ML2024
Posterior sampling via Langevin dynamics based on generative priors
Vishal Purohit, Matthew Repasky, Jianfeng Lu +3
Posterior sampling in high-dimensional spaces using generative models holds significant promise for various applications, including but not limited to inverse problems and guided g…
stat.ML2024
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
Xiuyuan Cheng, Jianfeng Lu, Yixin Tan +1
Flow-based generative models enjoy certain advantages in computing the data generation and the likelihood, and have recently shown competitive empirical performance. Compared to th…