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The MBPEP: a deep ensemble pruning algorithm providing high quality
  uncertainty prediction

The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction

25 February 2019
Ruihan Hu
Qijun Huang
Sheng Chang
Hao Wang
Jin He
    UQCV
ArXivPDFHTML

Papers citing "The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction"

6 / 6 papers shown
Title
SEF: A Method for Computing Prediction Intervals by Shifting the Error
  Function in Neural Networks
SEF: A Method for Computing Prediction Intervals by Shifting the Error Function in Neural Networks
E. V. Aretos
D. G. Sotiropoulos
25
0
0
08 Sep 2024
Benchmarking Scalable Epistemic Uncertainty Quantification in Organ
  Segmentation
Benchmarking Scalable Epistemic Uncertainty Quantification in Organ Segmentation
Jadie Adams
Shireen Elhabian
UQCV
18
5
0
15 Aug 2023
Uncertainty-Aware Null Space Networks for Data-Consistent Image
  Reconstruction
Uncertainty-Aware Null Space Networks for Data-Consistent Image Reconstruction
Christoph Angermann
Simon Göppel
Markus Haltmeier
28
2
0
14 Apr 2023
Exploring Uncertainty in Deep Learning for Construction of Prediction
  Intervals
Exploring Uncertainty in Deep Learning for Construction of Prediction Intervals
Yuandu Lai
Yucheng Shi
Yahong Han
Yunfeng Shao
Meiyu Qi
Bingshuai Li
UQCV
33
15
0
27 Apr 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
276
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
285
9,138
0
06 Jun 2015
1