You can directly edit(add/delete/modify) the README.md file for contribution. If you don't know how to edit the file, please leave a message to the Issue board.
- 2016 : +20 citations (:sparkles: +50)
- 2015 : +100 citations (:sparkles: +200)
- 2014 : +200 citations (:sparkles: +400)
- 2013 : +300 citations (:sparkles: +600)
- 2012 : +400 citations (:sparkles: +800)
- 2011 : +500 citations (:sparkles: +1000)
- 2010 : +600 citations (:sparkles: +1200)
This criteria is not a strict baseline, but a flexible guideline for being added to the awesome list. (Since the number of citations is affected by the research area, some papers under the threshold may be added to the list while some over the threshold may not.) If you add papers which are under the above criteria, please provide enough descrpitions which the papers should be added.
You can add / delete / modify the papers on the awesome list.
As mentioned above, please provide enough descrpitions when you push a request, especially for the papers which do not meet the criteria or for the papers for the Papers Worth Reading section.
Here is an example of markdown code for a paper on the list.
Distilling the knowledge in a neural network (2015), G. Hinton et al. [[pdf]](http://arxiv.org/pdf/1503.02531)
The pdf link which can directly download the pdf file rather than links to another webpage is preferred. If the number of authors are more than two, please write the first author's name only.
If a paper seems to be out-of-date or be a duplication of another paper, you can suggest deletion. Deletion is also an important contribution to maintain a tractable number of papers on the awesome list.
Modification (or Updates) that can usually happen is
- addition of ✨ marks (as increasing number of citations)
- addition of distingushed researchers
- move papers from a section from another
- correction of typo, grammatic error, etc.
Note that you are not allowed to add or modify the sections.
Thank you for all your contributions. You can also follow my facebook page or google plus to get useful information about machine learning and robotics. Thank you!
Terry