180 citations · 435 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
MRI Image Recovery using Damped Denoising Vector AMP
Subrata Sarkar, Rizwan Ahmad, Philip Schniter
Motivated by image recovery in magnetic resonance imaging (MRI), we propose a new approach to solving linear inverse problems based on iteratively calling a deep neural-network, so…
OCMR (v1.0)--Open-Access Multi-Coil k-Space Dataset for Cardiovascular Magnetic Resonance Imaging
Chong Chen, Yingmin Liu, Philip Schniter +5
Cardiovascular MRI (CMR) is a non-invasive imaging modality that provides excellent soft-tissue contrast without the use of ionizing radiation. Physiological motions and limited sp…
Sketching Datasets for Large-Scale Learning (long version)
Rémi Gribonval, Antoine Chatalic, Nicolas Keriven +3
This article considers "compressive learning," an approach to large-scale machine learning where datasets are massively compressed before learning (e.g., clustering, classification…
Free-breathing Cardiovascular MRI Using a Plug-and-Play Method with Learned Denoiser
Sizhuo Liu, Edward Reehorst, Philip Schniter +1
Cardiac magnetic resonance imaging (CMR) is a noninvasive imaging modality that provides a comprehensive evaluation of the cardiovascular system. The clinical utility of CMR is ham…
Inference in Multi-Layer Networks with Matrix-Valued Unknowns
Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan +2
We consider the problem of inferring the input and hidden variables of a stochastic multi-layer neural network from an observation of the output. The hidden variables in each layer…