6 papers
Picard Proximal Monte Carlo for Parallel Bayesian Imaging with Score-Based Generative Priors
Deliang Wei, Evan Bell, Wenhan Guo +2
Bayesian imaging inverse problems often require sampling from high-dimensional posterior distributions. While recent score-based and diffusion models provide expressive Bayesian pr…
VOLT: Volumetric Wide-Field Microscopy via 3D-Native Probabilistic Transport
Yetao He, Wenhan Guo, Deliang Wei +3
Three-dimensional (3D) wide-field fluorescence microscopy is a widely used modality for volumetric imaging, but suffers from characteristic out-of-focus blur. Existing reconstructi…
Tensor Completion via Monotone Inclusion: Generalized Low-Rank Priors Meet Deep Denoisers
Peng Chen, Deliang Wei, Jiale Yao +1
Missing entries in multi dimensional data pose significant challenges for downstream analysis across diverse real world applications. These data are naturally represented as tensor…
Provably Accelerated Imaging with Restarted Inertia and Score-based Image Priors
Marien Renaud, Julien Hermant, Deliang Wei +1
Fast convergence and high-quality image recovery are two essential features of algorithms for solving ill-posed imaging inverse problems. Existing methods, such as regularization b…
Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Inverse Problems
Deliang Wei, Peng Chen, Haobo Xu +3
Plug-and-play (PnP) methods with deep denoisers have shown impressive results in imaging problems. They typically require strong convexity or smoothness of the fidelity term and a…
Learning pseudo-contractive denoisers for inverse problems
Deliang Wei, Peng Chen, Fang Li
Deep denoisers have shown excellent performance in solving inverse problems in signal and image processing. In order to guarantee the convergence, the denoiser needs to satisfy som…