221 citations · 1.5k across the 104 of their papers we have counts for
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Plug-In Stochastic Gradient Method
Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a popular framework for regularized signal reconstruction by using advanced denoisers within an iterative algorithm. In this paper, we discuss our rec…
Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm
Yu Sun, Shiqi Xu, Yunzhe Li +3
The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser with…
Image Restoration using Total Variation Regularized Deep Image Prior
Jiaming Liu, Yu Sun, Xiaojian Xu +1
In the past decade, sparsity-driven regularization has led to significant improvements in image reconstruction. Traditional regularizers, such as total variation (TV), rely on anal…
An Online Plug-and-Play Algorithm for Regularized Image Reconstruction
Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a powerful framework for regularizing imaging inverse problems by using advanced denoisers within an iterative algorithm. Recent experimental evidence…
Holographic particle localization under multiple scattering
Waleed Tahir, Ulugbek S. Kamilov, Lei Tian
We introduce a novel framework that incorporates multiple scattering for large-scale 3D particle-localization using single-shot in-line holography. Traditional holographic techniqu…
signProx: One-Bit Proximal Algorithm for Nonconvex Stochastic Optimization
Xiaojian Xu, Ulugbek S. Kamilov
Stochastic gradient descent (SGD) is one of the most widely used optimization methods for parallel and distributed processing of large datasets. One of the key limitations of distr…