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QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted
  ensembles

QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles

19 April 2024
N. Ghanathe
Steve Wilton
    UQCV
ArXivPDFHTML

Papers citing "QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles"

4 / 4 papers shown
Title
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
173
875
0
21 Oct 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,561
0
17 Apr 2017
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
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
261
9,136
0
06 Jun 2015
1