1 code implementation • 13 May 2021 • Trung Le, Ryan Poplin, Fred Bertsch, Andeep Singh Toor, Margaret L. Oh
We introduce a new dataset called SyntheticFur built specifically for machine learning training.
4 code implementations • NeurIPS 2019 • Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
We propose a likelihood ratio method for deep generative models which effectively corrects for these confounding background statistics.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
no code implementations • 21 Dec 2017 • Avinash V. Varadarajan, Ryan Poplin, Katy Blumer, Christof Angermueller, Joe Ledsam, Reena Chopra, Pearse A. Keane, Greg S. Corrado, Lily Peng, Dale R. Webster
Mean absolute error (MAE) of the algorithm's prediction compared to the refractive error obtained in the AREDS and UK Biobank.
no code implementations • 31 Aug 2017 • Ryan Poplin, Avinash V. Varadarajan, Katy Blumer, Yun Liu, Michael V. McConnell, Greg S. Corrado, Lily Peng, Dale R. Webster
Traditionally, medical discoveries are made by observing associations and then designing experiments to test these hypotheses.