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Uncertainty Quantification for Sparse Deep Learning

Uncertainty Quantification for Sparse Deep Learning

26 February 2020
Yuexi Wang
Veronika Rockova
    BDL
    UQCV
ArXivPDFHTML

Papers citing "Uncertainty Quantification for Sparse Deep Learning"

7 / 7 papers shown
Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
L. J. L. Lopez
Shaza Elsharief
Dhiyaa Al Jorf
Firas Darwish
Congbo Ma
Farah E. Shamout
98
0
0
04 May 2025
Density Regression and Uncertainty Quantification with Bayesian Deep
  Noise Neural Networks
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks
Daiwei Zhang
Tianci Liu
Jian Kang
BDL
UQCV
26
2
0
12 Jun 2022
A Kernel-Expanded Stochastic Neural Network
A Kernel-Expanded Stochastic Neural Network
Y. Sun
F. Liang
17
5
0
14 Jan 2022
An Uncertainty-aware Loss Function for Training Neural Networks with
  Calibrated Predictions
An Uncertainty-aware Loss Function for Training Neural Networks with Calibrated Predictions
Afshar Shamsi
Hamzeh Asgharnezhad
AmirReza Tajally
Saeid Nahavandi
Henry Leung
UQCV
36
6
0
07 Oct 2021
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
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
128
602
0
14 Feb 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
279
9,136
0
06 Jun 2015
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