Name
Title | ||
|---|---|---|
ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility |
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-76423-4_1 | RRPR |
DocType | Citations | PageRank |
Conference | 1 | 0.38 |
References | Authors | |
12 | 12 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Burak Yildiz | 1 | 1 | 0.38 |
| Hayley Hung | 2 | 12 | 0.94 |
| Jesse H. Krijthe | 3 | 26 | 5.32 |
| Cynthia C. S. Liem | 4 | 1 | 0.38 |
| Marco Loog | 5 | 1796 | 154.31 |
| Gosia Migut | 6 | 1 | 0.72 |
| Frans A. Oliehoek | 7 | 397 | 40.32 |
| Annibale Panichella | 8 | 838 | 45.02 |
| Przemyslaw Pawelczak | 9 | 6 | 1.44 |
| Stjepan Picek | 10 | 6 | 5.82 |
| Mathijs de Weerdt | 11 | 1 | 0.38 |
| Jan van Gemert | 12 | 1 | 0.38 |