1 citations · 1 across the 5 of their papers we have counts for
6 papers
Solving Inverse Problems using Diffusion with Iterative Colored Renoising
Matt C. Bendel, Saurav K. Shastri, Rizwan Ahmad +1
Imaging inverse problems can be solved in an unsupervised manner using pre-trained diffusion models, but doing so requires approximating the gradient of the measurement-conditional…
Fast and Robust Phase Retrieval via Deep Expectation-Consistent Approximation
Saurav K. Shastri, Philip Schniter
Accurately recovering images from phaseless measurements is a challenging and long-standing problem. In this work, we present "deepECpr," which combines expectation-consistent (EC)…
Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery
Saurav K. Shastri, Rizwan Ahmad, Christopher A. Metzler +1
To solve inverse problems, plug-and-play (PnP) methods replace the proximal step in a convex optimization algorithm with a call to an application-specific denoiser, often implement…
Expectation Consistent Plug-and-Play for MRI
Saurav K Shastri, Rizwan Ahmad, Christopher A Metzler +1
For image recovery problems, plug-and-play (PnP) methods have been developed that replace the proximal step in an optimization algorithm with a call to an application-specific deno…
Autotuning Plug-and-Play Algorithms for MRI
Saurav K. Shastri, Rizwan Ahmad, Philip Schniter
For magnetic resonance imaging (MRI), recently proposed "plug-and-play" (PnP) image recovery algorithms have shown remarkable performance. These PnP algorithms are similar to tradi…
Generalized Design of Sampling Kernels for 2-D FRI Signals
Saurav Kumaraswami Shastri, Sunil Rudresh, Chandra Sekhar Seelamantula
One of the interesting problems in the finite-rate-of-innovation signal sampling framework is the design of compactly supported sampling kernels. In this paper, we present a generi…