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Underspecification Presents Challenges for Credibility in Modern Machine
  Learning

Underspecification Presents Challenges for Credibility in Modern Machine Learning

6 November 2020
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
Alex Beutel
Christina W. Chen
Jonathan Deaton
Jacob Eisenstein
Matthew D. Hoffman
F. Hormozdiari
N. Houlsby
Shaobo Hou
Ghassen Jerfel
Alan Karthikesalingam
Mario Lucic
Yi-An Ma
Cory Y. McLean
Diana Mincu
A. Mitani
Andrea Montanari
Zachary Nado
Vivek Natarajan
Christopher Nielson
T. Osborne
R. Raman
K. Ramasamy
Rory Sayres
Jessica Schrouff
Martin G. Seneviratne
Shannon Sequeira
Harini Suresh
Victor Veitch
Max Vladymyrov
Xuezhi Wang
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
    OffRL
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Papers citing "Underspecification Presents Challenges for Credibility in Modern Machine Learning"

1 / 351 papers shown
Title
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,660
0
05 Dec 2016
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