ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility
arXiv:2012.01172 · doi:10.1007/978-3-030-76423-4_1
Abstract
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.
Accepted to RRPR 2020: Third Workshop on Reproducible Research in Pattern Recognition