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Density Regression and Uncertainty Quantification with Bayesian Deep
  Noise Neural Networks

Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks

12 June 2022
Daiwei Zhang
Tianci Liu
Jian Kang
    BDL
    UQCV
ArXivPDFHTML

Papers citing "Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks"

3 / 3 papers shown
Title
Sparse Deep Learning: A New Framework Immune to Local Traps and
  Miscalibration
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Y. Sun
Wenjun Xiong
F. Liang
40
8
0
01 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
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
282
9,136
0
06 Jun 2015
1