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Dense Uncertainty Estimation via an Ensemble-based Conditional Latent
  Variable Model

Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model

22 November 2021
Jing Zhang
Yuchao Dai
Mehrtash Harandi
Yiran Zhong
Nick Barnes
Richard I. Hartley
    UQCV
ArXivPDFHTML

Papers citing "Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model"

9 / 9 papers shown
Title
Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image
  Enhancement
Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement
Uddeshya Upadhyay
Viswanath P. Sudarshan
Suyash P. Awate
MedIm
49
21
0
07 Oct 2021
Correlated Input-Dependent Label Noise in Large-Scale Image
  Classification
Correlated Input-Dependent Label Noise in Large-Scale Image Classification
Mark Collier
Basil Mustafa
Efi Kokiopoulou
Rodolphe Jenatton
Jesse Berent
NoLa
181
53
0
19 May 2021
DEUP: Direct Epistemic Uncertainty Prediction
DEUP: Direct Epistemic Uncertainty Prediction
Salem Lahlou
Moksh Jain
Hadi Nekoei
V. Butoi
Paul Bertin
Jarrid Rector-Brooks
Maksym Korablyov
Yoshua Bengio
PER
UQLM
UQCV
UD
202
81
0
16 Feb 2021
Learning Accurate Dense Correspondences and When to Trust Them
Learning Accurate Dense Correspondences and When to Trust Them
Prune Truong
Martin Danelljan
Luc Van Gool
Radu Timofte
3DH
3DPC
79
128
0
05 Jan 2021
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Lingkai Kong
Jimeng Sun
Chao Zhang
UQCV
50
103
0
24 Aug 2020
Scalable Uncertainty for Computer Vision with Functional Variational
  Inference
Scalable Uncertainty for Computer Vision with Functional Variational Inference
Eduardo D C Carvalho
R. Clark
Andrea Nicastro
Paul H. J. Kelly
BDL
UQCV
131
22
0
06 Mar 2020
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
5,661
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
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,266
0
09 Jun 2012
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