compressed sensing

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Most implemented papers archive 2025-07-28

30 shown of 246 papers with code (992 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
  1 Dec 2022 4 repositories listed Syntology ran 12 of 23 samples · 11 unverified
  Most existing Image Restoration (IR) models are task-specific, which can not be generalized to different degradation operators.
• ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data
  16 Mar 2021 4 repositories listed
  It has been shown that the proposed framework can successfully reconstruct even for an acceleration factor of 20 for Cartesian (0.
• Accelerated MRI with Un-trained Neural Networks
  6 Jul 2020 4 repositories listed
  Convolutional Neural Networks (CNNs) are highly effective for image reconstruction problems.
• A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
  8 Apr 2017 4 repositories listed
  Firstly, we show that when each 2D image frame is reconstructed independently, the proposed method outperforms state-of-the-art 2D compressed sensing approaches such as dictionary learning-based MR image reconstruction,…
• A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction
  1 Mar 2017 4 repositories listed
  The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow.
• Leveraging Memory Effects and Gradient Information in Consensus-Based Optimization: On Global Convergence in Mean-Field Law
  22 Nov 2022 3 repositories listed
  In this paper we study consensus-based optimization (CBO), a versatile, flexible and customizable optimization method suitable for performing nonconvex and nonsmooth global optimizations in high dimensions.
• Quantized Compressed Sensing with Score-based Generative Models
  2 Nov 2022 3 repositories listed
  We consider the general problem of recovering a high-dimensional signal from noisy quantized measurements.
• Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction
  18 Nov 2021 3 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 2 pointer-only (licence)
  Magnetic Resonance Imaging can produce detailed images of the anatomy and physiology of the human body that can assist doctors in diagnosing and treating pathologies such as tumours.
• End-to-End Variational Networks for Accelerated MRI Reconstruction
  14 Apr 2020 3 repositories listed Syntology ran 1 of 5 samples · 4 unverified
  The slow acquisition speed of magnetic resonance imaging (MRI) has led to the development of two complementary methods: acquiring multiple views of the anatomy simultaneously (parallel imaging) and acquiring fewer…
• Explaining Groups of Points in Low-Dimensional Representations
  3 Mar 2020 3 repositories listed
  A common workflow in data exploration is to learn a low-dimensional representation of the data, identify groups of points in that representation, and examine the differences between the groups to determine what they…
• IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
  24 Sep 2019 3 repositories listed
  To improve the compressive sensing MRI (CS-MRI) approaches in terms of fine structure loss under high acceleration factors, we have proposed an iterative feature refinement model (IFR-CS), equipped with fixed…
• Cell Detection in Microscopy Images with Deep Convolutional Neural Network and Compressed Sensing
  10 Aug 2017 3 repositories listed
  In this paper, we seek a different route and propose a convolutional neural network (CNN)-based cell detection method that uses encoding of the output pixel space.
• Compressed Sensing using Generative Models
  9 Mar 2017 3 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  The goal of compressed sensing is to estimate a vector from an underdetermined system of noisy linear measurements, by making use of prior knowledge on the structure of vectors in the relevant domain.
• Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
  29 May 2024 2 repositories listed Syntology ran 7 of 13 samples · 6 unverified
  We validate our approach for various linear inverse problems, such as super-resolution, deblurring, inpainting, and compressed sensing, and demonstrate that we can outperform other methods based on flow matching.
• Investigating the use of publicly available natural videos to learn Dynamic MR image reconstruction
  23 Nov 2023 2 repositories listed
  Purpose: To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K).
• Generative Priors for MRI Reconstruction Trained from Magnitude-Only Images Using Phase Augmentation
  4 Aug 2023 2 repositories listed
  Purpose: In this work, we present a workflow to construct generic and robust generative image priors from magnitude-only images.
• AutoSamp: Autoencoding k-space Sampling via Variational Information Maximization for 3D MRI
  5 Jun 2023 2 repositories listed
  Experiments on public 3D acquired MRI datasets show improved reconstruction quality of the proposed AutoSamp method over the prevailing variable density and variable density Poisson disc sampling for both compressed…
• Ambient Diffusion: Learning Clean Distributions from Corrupted Data
  30 May 2023 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  We present the first diffusion-based framework that can learn an unknown distribution using only highly-corrupted samples.
• QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative Models
  2 Feb 2023 2 repositories listed
  In practical compressed sensing (CS), the obtained measurements typically necessitate quantization to a limited number of bits prior to transmission or storage.
• A unified model for reconstruction and R2* mapping of accelerated 7T data using the quantitative recurrent inference machine
  12 Oct 2022 2 repositories listed
  With increasing acceleration factor, an increasing reduction in the reconstruction error was observed, pointing to a larger benefit for sparser data.
• Self-supervised deep image restoration via adaptive stochastic gradient Langevin dynamics
  19 Jun 2022 2 repositories listed
  While supervised deep learning has been a prominent tool for solving many image restoration problems, there is an increasing interest on studying self-supervised or un- supervised methods to address the challenges and…
• Technical Report (v1.0)--Pseudo-random Cartesian Sampling for Dynamic MRI
  8 Jun 2022 2 repositories listed
  For an effective application of compressed sensing (CS), which exploits the underlying compressibility of an image, one of the requirements is that the undersampling artifact be incoherent (noise-like) in the…
• MIMO Channel Estimation using Score-Based Generative Models
  14 Apr 2022 2 repositories listed
  We introduce a framework for training score-based generative models for wireless MIMO channels and performing channel estimation based on posterior sampling at test time.
• Computing Multiple Image Reconstructions with a Single Hypernetwork
  22 Feb 2022 2 repositories listed
  The typical approach is to train the model for a hyperparameter setting determined with some empirical or theoretical justification.
• Efficient approximation of Jacobian matrices involving a non-uniform fast Fourier transform (NUFFT)
  4 Nov 2021 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  In fact, we show that model-based image reconstruction (MBIR) methods with suitably optimized imaging parameters can perform nearly as well as CNN-based methods.
• Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results
  16 Sep 2021 2 repositories listed
  We demonstrate this phenomenon for inverse problem solvers and show how their biased performance stems from hidden data preprocessing pipelines.
• Robust Compressed Sensing MRI with Deep Generative Priors
  3 Aug 2021 2 repositories listed
  The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep generative priors can be powerful tools for solving inverse problems.
• Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
  15 Feb 2021 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  We propose Intermediate Layer Optimization (ILO), a novel optimization algorithm for solving inverse problems with deep generative models.
• B-spline Parameterized Joint Optimization of Reconstruction and K-space Trajectories (BJORK) for Accelerated 2D MRI
  27 Jan 2021 2 repositories listed
  Though trained with neural network-based reconstruction, the proposed trajectory also leads to improved image quality with compressed sensing-based reconstruction.
• Preconditioned training of normalizing flows for variational inference in inverse problems
  11 Jan 2021 2 repositories listed
  Obtaining samples from the posterior distribution of inverse problems with expensive forward operators is challenging especially when the unknowns involve the strongly heterogeneous Earth.

Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.