Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction: Implementation & Demo

Python package for signal processing, with emphasis on iterative methods

(TPAMI 2025) Invertible Diffusion Models for Compressed Sensing [PyTorch]

[ICML 2021] Official implementation: Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

(TPAMI 2024) Practical Compact Deep Compressed Sensing [PyTorch]

(IJCV 2024) Self-Supervised Scalable Deep Compressed Sensing [PyTorch]

[NeurIPS 2021] SNIPS: Solving Noisy Inverse Problems Stochastically

TensorFlow implementation of descrete wavelets transforms

A Deep Learning Approach to Ultrasound Image Recovery

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning

A package for AFM image reconstruction and compressed sensing in general

(TIP 2022) Content-aware Scalable Deep Compressed Sensing [PyTorch]

(IJCV 2023) Deep Physics-Guided Unrolling Generalization for Compressed Sensing [PyTorch]

Code for "Adversarial and Perceptual Refinement Compressed Sensing MRI Reconstruction"

Task-Aware Compressed Sensing Using Generative Adversarial Networks (published in AAAI18)

(Nature Communications Engineering 2024) Compressive Confocal Microscopy Imaging at the Single-Photon Level with Ultra-Low Sampling Ratios [PyTorch]

Implementation of IEEE 2019 Research Paper : Image Compressed Sensing using Convolutional Neural Network.

Source code for the paper "Deep Learning Sparse Ternary Projections For Compressed Sensing of Images"

A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.

Chaotic Sensing (ChaoS)