GitXiv: Because People Still Don't Care About You and Your Algorithm

If you have followed Nuit Blanche long enough, you know that I take a specific interest in papers that release an attendant implementation. As a matter of fact, each implementation released in the wild is listed under the implementation tag (and shown prominently every end of the month in the Nuit Blanche monthly reviews). 

Since 2012, Nuit Blanche has featured  380 blog entries with one implementation.

Much like the listing of codes available in the Big Picture in Compressive Sensing, the Advanced Matrix Factorization Jungle Page, the Reproducible Research page (yes, they need updating, I know), it seems obvious there is a similar need for Machine Learning. The field itself is facing a similar problem as compressive sensing on the issue of reproducible research. 

Enter GitXiv by Samim (Samim Winiger) and graphific ( Roelof Pieters ) from the site "About page"

GitXiv — Collaborative Open Computer Science

In recent years, a highly interesting pattern has emerged: Computer scientists release new research findings on arXiv and just days later, developers release an open-source implementation on GitHub. This pattern is immensely powerful. One could call it collaborative open computer science (cocs).

GitXiv is a space to share links to open computer science projects. Countless Github and arXiv links are floating around the web. Its hard to keep track of these gems. GitXiv attempts to solve this problem by offering a collaboratively curated feed of projects. Each project is conveniently presented as arXiv + Github + Links + Discussion. Members can submit their findings and let the community rank and discuss it. A regular newsletter makes it easy to stay up-to-date on recent advancements. It´s free and open. Read more...

• The GitXiv website is open-source.

• For ideas/bugs/feature requests, open a Issue.

• Collaborate & discuss on the Wiki.

• GitXiv has a RSS feed.

• The site was created by Samim. Get in touch.

   

Samim and Roelof kindly added Compressive Sensing but there are also categories such as Matrix Factorization  or Dimensionality Reduction and more.

Of related interest:

• What Could Possibly Go Wrong ? Peer-Review, Trolls, Data Breaches
• Reddit, Google+, LinkedIn as Peer Review Systems
• Nobody Cares About You and Your Algorithm
• It's Not Me, It's You

    Join the CompressiveSensing subreddit or the Google+ Community or the Facebook page and post there !
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