ReproducedPapers.org
Openly Teaching and Structuring Machine Learning Reproducibility
Burak Yildiz (TU Delft - Pattern Recognition and Bioinformatics)
Hayley Hung (TU Delft - Pattern Recognition and Bioinformatics)
Jesse H. Krijthe (TU Delft - Pattern Recognition and Bioinformatics)
Cynthia C.S. Liem (TU Delft - Multimedia Computing)
Marco Loog (TU Delft - Pattern Recognition and Bioinformatics)
Gosia Migut (TU Delft - Computer Science & Engineering-Teaching Team)
Frans A. Oliehoek (TU Delft - Interactive Intelligence)
Annibale Panichella (TU Delft - Software Engineering)
Przemysław Pawełczak (TU Delft - Embedded Systems)
Stjepan Picek (TU Delft - Cyber Security)
Mathijs de Weerdt (TU Delft - Algorithmics)
Jan van Gemert (TU Delft - Pattern Recognition and Bioinformatics)
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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.