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Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties

Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties

5 May 2025
Jiaxiang Yi
Miguel A. Bessa
    UDPERUQCV
ArXiv (abs)PDFHTML

Papers citing "Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties"

15 / 15 papers shown
Title
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for
  Specialized Tasks
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
Bálint Mucsányi
Michael Kirchhof
Seong Joon Oh
UQCVBDLOODD
557
31
1
29 Feb 2024
Optimal Training of Mean Variance Estimation Neural Networks
Optimal Training of Mean Variance Estimation Neural Networks
Laurens Sluijterman
Eric Cator
Tom Heskes
DRL
73
27
0
17 Feb 2023
A Review of Uncertainty Quantification in Deep Learning: Techniques,
  Applications and Challenges
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Li Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDLUQCV
353
1,935
0
12 Nov 2020
Uncertainty-Aware Deep Classifiers using Generative Models
Uncertainty-Aware Deep Classifiers using Generative Models
Murat Sensoy
Lance M. Kaplan
Federico Cerutti
Maryam Saleki
UQCVOOD
130
75
0
07 Jun 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier
Willem Waegeman
PERUD
258
1,432
0
21 Oct 2019
Deep Evidential Regression
Deep Evidential Regression
Alexander Amini
Wilko Schwarting
A. Soleimany
Daniela Rus
EDLPERBDLUDUQCV
103
442
0
07 Oct 2019
Reliable training and estimation of variance networks
Reliable training and estimation of variance networks
N. Detlefsen
Martin Jørgensen
Søren Hauberg
UQCV
103
89
0
04 Jun 2019
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,877
0
14 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer
  Vision?
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall
Y. Gal
BDLOODUDUQCVPER
362
4,721
0
15 Mar 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
UQCVBDL
847
5,847
0
05 Dec 2016
Scalable Bayesian Learning of Recurrent Neural Networks for Language
  Modeling
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling
Zhe Gan
Chunyuan Li
Changyou Chen
Yunchen Pu
Qinliang Su
Lawrence Carin
BDLUQCV
99
41
0
23 Nov 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,641
0
10 Dec 2015
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
UQCVBDL
891
9,364
0
06 Jun 2015
Weight Uncertainty in Neural Networks
Weight Uncertainty in Neural Networks
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
UQCVBDL
192
1,894
0
20 May 2015
Learning Phrase Representations using RNN Encoder-Decoder for
  Statistical Machine Translation
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho
B. V. Merrienboer
Çağlar Gülçehre
Dzmitry Bahdanau
Fethi Bougares
Holger Schwenk
Yoshua Bengio
AIMat
1.1K
23,414
0
03 Jun 2014
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