This page tries to list most of the Compressive sites that are doing a good outreach to newcomers. They are not exhaustive and I look forward to new additions (please contact me).

1. Codes with Examples

All the Compressive Sensing codes are available here. However, some groups have put an extra effort at featuring examples on how their code work  directly on their webpage. This following list comprises this subset:

• SPARCO: A toolbox for testing sparse reconstruction algorithms: Examples and problems treated in Sparco can be found here.
  
• l1-Magic: Examples can be found here.
  
• SparseLab: Examples can be found here.
• GPSR: An example is shown in the main page.
  
• SPGL1: A solver for large scale sparse reconstruction: Examples can be found here.
  
• TwIST: Examples can be found on the main page.
  
• Chambolle's algorithm for the resolution of compressed sensing with TV regularization by Gabriel Peyre. This algorithm is included in the larger Toolbox Sparsity - A toolbox for sparse coding and sparse regularization
• Wiki on Sparse Recovery Experiments with attendant code.
• Fast Bayesian Matching Pursuit: examples are given here.
• Toolbox Sparsity - A toolbox for sparse coding and sparse regularization.
  
• Algorithm implementing the search for the JN condition explained in On Verifiable Sufficient Conditions for Sparse Signal Recovery via l_1 Minimization
•  Compressive Sensing via Belief Propagation website and code.
• Locally produced codes also listed here with links to examples.
  

2. Websites presenting CS work

There are also pages specifically dedicated to featuring Compressive Sensing by research groups/authors:

• The Rice group led by Richard Baraniuk has been the leader in spearheading information diffusion on the subject of compressive sensing through their Rice Compressive Sensing Resource page.  They also have a nice presentation of the now famous Rice Single pixel camera.
• Terry Tao has made a list of the different matrices and their properties wrt compressive sensing in this page: Preprints in sparse recovery / Summary of properties of random matrices.
• Face Recognition via Sparse Representation led by Yi Ma at UIUC and Feature Selection in Face Recognition: A Sparse Representation Perspective led by Allen Yang at Berkeley.
  
• Duke DISP lab  led by David Brady. Of particular interest is Ashwin Wagadarikar's page on the compressive sensing hyperspectral imager.
• Compressive Optical Systems, NISLab led by Rebecca Willett at Duke.
  
• Gabriel Peyre,  Chambolle's algorithm for the resolution of compressed sensing with TV regularization. 
• Dror Baron's Compressed Sensing site.
  

3. Blogs and Wiki related to CS

Finally, this is a list of Blogs and wikis with specific tags on compressive sensing.

• Terry Tao blog on compressive sensing
• Corrada-Emmanuel entitled De Rerum Natura
• The Geomblog by Piotr Indyk and Suresh
• Laurent Jacques, Le petit chercheur illustre
• Andriyan Suksmono, Chaotic Pearls (in Indonesian)  
• Wikimization (http://wikimization.org) is a repository and resource for all things Optimization. Created by Jon Dattorro
  
• Valerio Cambareri, Studies in Information Engineering

• Gabriel Peyre released a set of matlab experiments to illustrate the 3rd edition of the "A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way" book of Stephane Mallat, which will feature chapters about sparse representations and compressive sensing. A "beta version" of the experiments is available at: http://www.ceremade.dauphine.fr/~peyre/wavelet-tour/

• Nuit Blanche on Compressive Sensing