Definitions, methods, and applications in interpretable machine learning
W. James Murdoch, Chandan Singh, Karl Kumbier, Reza Abbasi-Asl, and Bin YuPNAS (Proceedings of the National Academy of Sciences of the United States of America)
October 16, 2019
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia
Aaron Halfaker, R. Stuart GeigerarXiv.org
September 11, 2019
The Rise and Fall of the Note: Changing Paper Lengths in ACM CSCW, 2000-2018
R. Stuart GeigerarXiv.org
August 28, 2019
The representation of semantic information across human cerebral cortex during listening versus reading is invariant to stimulus modality
Fatma Deniz, Anwar O. Nunez-Elizalde, Alexander G. Huth and Jack L. GallantJournal of Neuroscience
August 19, 2019
Human Health and the Social Cost of Carbon: A Primer and Call to Action
Noah Scovronick, Valeri N. Vasquez, Frank Errickson, Francis Dennig, Antonio Gasparrini, Shakoor Hajat, Dean Spears, Mark B. BudolfsonEpidemiology
August 15, 2019
Transparent and Reproducible Social Science Research: How to Do Open Science
Garret Christensen, Jeremy Freese, and Edward MiguelUniversity of California Press
July 23, 2019
Multivariate GWAS: Generalized Linear Models, Prior Weights, and Double Sparsity
Benjamin B. Chu, Kevin L. Keys, Janet S. Sinsheimer, Kenneth LangebioRxiv
July 11, 2019
Computing water flow through complex landscapes, Part 2: Finding hierarchies in depressions and morphological segmentations
Richard Barnes, Kerry L. Callaghan, and Andrew D. WickertEarth Surface Dynamics
June 17, 2019
Deep learning for single-shot autofocus microscopy
Henry Pinkard, Zachary Phillips, Arman Babakhani, Daniel A. Fletcher, Laura WallerOptica
June 5, 2019