We present ReproducedPapers.org : an open online repository for teaching and structuring machine learning reproducibility. We evaluate doing a reproduction project among students and the added value of an online reproduction repository among AI researchers. We use anonymous self-assessment surveys and obtained 144 responses. Results suggest that students who do a reproduction project place more value on scientific reproductions and become more critical thinkers. Students and AI researchers agree that our online reproduction repository is valuable.
|Title of host publication||Reproducible Research in Pattern Recognition - 3rd International Workshop, RRPR 2021, Revised Selected Papers|
|Editors||Bertrand Kerautret, Miguel Colom, Adrien Krähenbühl, Daniel Lopresti, Pascal Monasse, Hugues Talbot|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||9|
|Publication status||Published - 2021|
|Event||3rd International Workshop on Reproducible Research in Pattern Recognition, RRPR 2021 - Virtual, Online|
Duration: 11 Jan 2021 → 11 Jan 2021
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||3rd International Workshop on Reproducible Research in Pattern Recognition, RRPR 2021|
|Period||11/01/21 → 11/01/21|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
- Machine learning
- Online repository