2.4k citations · 4k across the 15 of their papers we have counts for
Showing 2020Show all
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cs.LG2020★ 285 cited
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund +20
Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the…
stat.AP2020★ 533 cited
The importance of transparency and reproducibility in artificial intelligence research
Benjamin Haibe-Kains, George Alexandru Adam, Ahmed Hosny +17
In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening. However, the lack of detailed methods and computer code undermines…