Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues

24 February 2023

Papers citing "Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues"

5 / 5 papers shown

Title
Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers Harald Semmelrock Tony Ross-Hellauer Simone Kopeinik Dieter Theiler Armin Haberl Stefan Thalmann Dominik Kowald 65 6 0 20 Jun 2024
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 117 355 0 04 Oct 2021
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging Karim Lekadira Richard Osuala C. Gallin Noussair Lazrak Kaisar Kushibar ... Nickolas Papanikolaou Zohaib Salahuddin Henry C. Woodruff Philippe Lambin L. Martí-Bonmatí AI4TS 63 56 0 20 Sep 2021
Anti-Distillation: Improving reproducibility of deep networks G. Shamir Lorenzo Coviello 34 20 0 19 Oct 2020
EGAD! an Evolved Grasping Analysis Dataset for diversity and reproducibility in robotic manipulation D. Morrison Peter Corke Jurgen Leitner 105 135 0 03 Mar 2020