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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
Local Flow Matching Generative Models
Chen Xu, Xiuyuan Cheng, Yao Xie
Flow Matching (FM) is a simulation-free method for learning a continuous, invertible flow that interpolates between two distributions, and in particular generates data from noise.…