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Non-linear Recovery of Sparse Signal Representations with Applications to Temporal and Spatial Localization

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Non-linear Recovery of Sparse Signal Representations with Applications to Temporal and Spatial Localization

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Quantification Of Resting-State Fmri Networks Driven By Hemodynamically Informed Spatiotemporal Regularization

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

A compressed-sensing approach for ultrasound imaging

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Learning Data Triage: Linear Decoding Works for Compressive MRI

Signal structure: from manifolds to molecules and structured sparsity

Tutorial: Sub-Nyquist artifacts and sampling moiré effects

Image Reconstruction in K-Space from MR Data Encoded with Ambiguous Gradient Fields

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Quantification Of Resting-State Fmri Networks Driven By Hemodynamically Informed Spatiotemporal Regularization

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Tutorial: Sub-Nyquist artifacts and sampling moiré effects

Learning Data Triage: Linear Decoding Works for Compressive MRI

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

A compressed-sensing approach for ultrasound imaging

Signal structure: from manifolds to molecules and structured sparsity

Image Reconstruction in K-Space from MR Data Encoded with Ambiguous Gradient Fields