What conferences want: reproducibility of experiments in data science

Leading scientific conferences ask for reproducibility of experiments. And this is necessary to increase the credibility of the work, to extract value (reusability and citation), well, and the "trend" ( according to a survey of the journal Nature ).





Expectations are growing, in 2021 already 9 out of 10 conferences offer authors to be checked for reproducibility. Pass the test, fill out a questionnaire, bring a witness, etc. 





What we are talking about, why reproducibility is needed, what problems need to be solved, we will discuss in this article. 





Experiments in machine learning

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, AAAI 2014, AAAI 2016, IJCAI 2013 IJCAI 2016 , 80% โ€” !





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2021 . GuideToResearch (Top 100), Machine Learning, Data Mining & Artificial Intelligence. .





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1





CVPR 2020





http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines





Encouraged





2





NeurIPS 2021





https://neurips.cc/Conferences/2021/PaperInformation/PaperChecklist





Required





3





ICCV 2021





http://iccv2021.thecvf.com/node/4





Encouraged





4





ECCV 2020





https://eccv2020.eu/reviewer-instructions/





Encouraged





5





AAAI 2021





https://aaai.org/Conferences/AAAI-21/aaai21call/





Required





6





ICML 2021





https://icml.cc/Conferences/2021/CallForPapers





Encouraged





7





SIGKDD 2021





https://www.kdd.org/kdd2020/files/KDD_2020_Call_for_Research_Papers.pdf





Encouraged





8





IJCAI 2021





https://ijcai-21.org/cfp/





Required





9





ICLR 2021





https://iclr.cc/Conferences/2021/CallForPapers





Not found





10





ACL 2021





https://2021.aclweb.org/calls/papers/





Reminder





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  • Not found โ€” CFP .





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(repeatable experiment / )

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(reproducible / )

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, - https://en.wikipedia.org/wiki/Reproducibility





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โ€œnon-reproducible single occurrences are of no significance to scienceโ€





โ€” Popper, K. R. 1959. The logic of scientific discovery. Hutchinson, London, United Kingdom.





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Jupyter Notebooks, GitHub, , 4% .





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A Large-scale Study about Quality and Reproducibility of Jupyter Notebooks.





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[5] Jupyter Notebooks. 





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[7]  , Best Practices for Scientific Computing





[8] Top Ten Reasons (not) to Share your Research Code .





[9] An article with survey results that has a greater impact on reproducibility, Understanding experiments and research practices for reproducibility: an exploratory study








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