# Reproducibility and replicability

Out of the 159 papers listed in this repository, only 41 articles provide their source code.
Repeatability is the key to good science.
Below is a list of useful links for reproducibility and replicability in Science:

- [DLPaper2Code: Auto-generation of Code from Deep Learning Research Papers](https://arxiv.org/abs/1711.03543)
- [Audio Processing Seminar 2016: Reproducible Research](https://github.com/audiolabs/APSRR-2016)
- [Reproducible Research in Signal Processing - What, why, and how](https://infoscience.epfl.ch/record/136640)
- [List of Reproducible Audio Research Papers ](https://github.com/faroit/reproducible-audio-research)
- [ReScience initiative](https://rescience.github.io/)
- [Workshop on reproducibility and replication in ML](https://sites.google.com/view/icml-reproducibility-workshop/home)
- [ICLR 2018 Reproducibility Challenge](http://www.cs.mcgill.ca/~jpineau/ICLR2018-ReproducibilityChallenge.html)
- [Reproducibility in Machine Learning-Based Studies: An Example of Text Mining](https://openreview.net/pdf?id=By4l2PbQ-)
- [Nature's insights on reproducibility](http://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970?WT.mc_id=FBK_NatureNews)
- [The titans of AI are getting their work double-checked by students](https://qz.com/1118671/the-titans-of-ai-are-getting-their-work-double-checked-by-students/)
- [Anonymous GitHub for double-blind peer-review](https://github.com/tdurieux/anonymous_github/)
- [Automated collection and reporting of citations for used software/methods/datasets](https://github.com/duecredit/duecredit)
- [EvalAI](https://github.com/Cloud-CV/EvalAI) - Evaluating state of the art in AI
- [Open Science List](https://github.com/INRIA/awesome-open-science-software) - Awesome open list of pointers about open science for software and computational science
- [Twitter post](https://twitter.com/goodfellow_ian/status/935886522607271937) - Advice from Ian Goodfellow
- [Dissemin](https://dissem.in/) - Open Access facilitator from [Dissemin](https://twitter.com/disseminOA/status/923469525827440641)
- [Do software and data products advance biology more than papers?](http://ivory.idyll.org/blog/2018-software-and-data-better-than-papers.html)
- [Before reproducibility must come preproducibility](https://www.nature.com/articles/d41586-018-05256-0?utm_source=twt_nnc&utm_medium=social&utm_campaign=naturenews&sf190281917=1) - Science should be ‘show me’, not ‘trust me’; it should be ‘help me if you can’, not ‘catch me if you can’.