Bayesian Orthogonal Matching Pursuit (Bernoulli-Gaussian)
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Updated
Aug 11, 2019 - MATLAB
Bayesian Orthogonal Matching Pursuit (Bernoulli-Gaussian)
A recursive framework to enhance the efficiency of deep unfolding networks.
My project for the MAT2000 course at UiO. De facto bachelor thesis.
Presentation for the exam of Optimal Control within the PhD program in Information Engineering of the Department of Information Engineering @ University of Pisa, A.A. 2021/2022
Injecting image priors into Learnable Compressive Subsampling
Undergraduate thesis on compressive sensing
Algorithms of compressive sensing like Orthogonal Matching Pursuit (OMP) and Subspace Pursuit (SP) in C
Research Project under the guidance of Professor Ajit Rajwade
GETS: a Genomic Tree based Sparse solver. This package accompanies an article to be published in the forthcoming Birkhäuser-ANHA book "Explorations in the Mathematics of Data Science" --- "A genomic tree based sparse solver" by Timothy A. Davis and Srinivas Subramanian.
Sampling-Priors-Augmented Deep Unfolding Network for Robust Video Compressive Sensing
Python wrapper for the fast TV denoising algorithm by Laurent Condat
The Generative Patch Prior for Compressive Image Recovery
This is a python package to perform progressive refinement method for sparse recovery (PRIS)
Early stages of incorporating self-supervised with algorithm unrolling. Code was written as part of a master's thesis (60 ECTS) at Aalborg University, Denmark.
Operational Support Estimator Networks (OSENs) are generic networks that can used in different support estimation problems.
Memory-Efficient Network for Large-scale Video Compressive Sensing, CVPR 2021
Novel image compression–encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing
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