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What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel
22 February 2023
Yao Qin
Xuezhi Wang
Balaji Lakshminarayanan
Ed H. Chi
Alex Beutel
UQCV
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Papers citing
"What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel"
5 / 5 papers shown
Title
Robust Classification by Coupling Data Mollification with Label Smoothing
Markus Heinonen
Ba-Hien Tran
Michael Kampffmeyer
Maurizio Filippone
70
0
0
03 Jun 2024
Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective
Bhagyashree Puranik
Ahmad Beirami
Yao Qin
Upamanyu Madhow
AAML
20
0
0
02 Nov 2023
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
296
39,194
0
01 Sep 2014
1