Very interesting! Reproducibility is VERY weak in the machine learning community, and needs to be improved.
---------- Forwarded message ---------- From: Nicolas P. Rougier Nicolas.Rougier@inria.fr Date: 2015-09-03 8:57 GMT-04:00 Subject: Connectionists: The ReScience journal To: Connectionists group connectionists@cs.cmu.edu
It's our great pleasure to announce the creation of "ReScience" which is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible.
To achieve such a goal, the whole editing chain is radically different from any other traditional scientific journal. ReScience lives on GitHub where each new implementation is made available together with comments, explanations and tests. Each submission takes the form of a pull request that is publicly reviewed and tested in order to guarantee that any researcher can re-use it.
Students are strongly encourage to submit to ReScience. Even if the publishing model is a bit different from other academic journals, this will give them a first experience at peer-reviewed publishing where they have to use a rigorous and scientific approach.
• More on the journal website: https://github.com/ReScience/ReScience/wiki • Current issue: https://github.com/ReScience/ReScience/wiki/Current-Issue • FAQ: https://github.com/ReScience/ReScience/wiki/Frequently-Asked-Questions • Follow us on twitter (@ReScienceEds): https://twitter.com/rescienceeds
And if you're familiar with Git and GitHub, you can also become a reviewer: just contact us.
Konrad Hinsen & Nicolas Rougier