new_org/releasing-research-code
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Tune wording

Browse Source
This commit is contained in:
Robert Stojnic
2020-04-06 16:39:24 +01:00
parent f688f963f8
commit ac1ba0cf71
2 changed files with 12 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
README.md
View File

@@ -1,6 +1,10 @@
# Resources for Code Release in Machine Learning
This repository contains resources for those wanting to publish a high impact ML research repository.
This repository contains official **NeurIPS 2020 code submission** resources.
For NeurIPS 2020 code submissions we recommend using a [README.md template](#readmemd-template) and checking as many items on the [ML Code Completeness Checklist](#ml-code-completeness-checklist) as possible.
The recommendation is based on a [data-driven analysis](https://medium.com/paperswithcode) of what makes a research code repository have high impact.
## README.md template
@@ -24,6 +28,8 @@ The checklist is made to be as general as possible. It consists of five items:
4. Table/Figure of the main result, with instruction to reproduce it
5. Pre-trained model
We found that NeurIPS 2019 repositories that have all five of these components got the highest number of GitHub stars.
We'll explain each one in some detail below.
#### 1. Specification of dependencies
@@ -60,7 +66,7 @@ Another common use case is fine-tuning for downstream task, where it's useful to
Lastly, some users might want to try out your model to see if it works on some example data. Providing pre-trained models allows your users to play around with your work and aids understanding of the paper's achievements.
## Awesome resources for releasing research code
## Other awesome resources for releasing research code
### Hosting pretrained models files

5
templates/README.md
View File

@@ -4,7 +4,7 @@
This repository is the official implementation of [My Paper Title](https://arxiv.org/abs/2030.12345).
> 📋Optional: include a graphic explaining your approach/main result and the bibtex entry
> 📋Optional: include a graphic explaining your approach/main result, bibtex entry, link to demos, blog posts and tutorials
## Requirements
@@ -57,3 +57,6 @@ Our model achieves the following performance on :
> 📋Include a table of results from your paper, and link back to the leaderboard for clarity and context. If your main result is a figure, include that figure and link to the command or notebook to reproduce it.
## Contributing
> 📋Pick a licence and describe how to contribute to your code repository.