3 papers
cs.LG2026
Exact Posterior Score Estimation for Solving Linear Inverse Problems
Abbas Mammadov, Ozgur Kara, Kaan Oktay +5
Diffusion and flow-based models learn powerful data priors by training a denoiser to reverse Gaussian corruption. To use this prior to solve a linear inverse problem, one needs to…
cs.CV2026
Variational Flow Maps: Make Some Noise for One-Step Conditional Generation
Abbas Mammadov, So Takao, Bohan Chen +4
Flow maps enable high-quality image generation in a single forward pass. However, unlike iterative diffusion models, their lack of an explicit sampling trajectory impedes incorpora…
cs.LG2025
Guided Diffusion Sampling on Function Spaces with Applications to PDEs
Jiachen Yao, Abbas Mammadov, Julius Berner +4
We propose a general framework for conditional sampling in PDE-based inverse problems, targeting the recovery of whole solutions from extremely sparse or noisy measurements. This i…