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Unlabelled Data Improves Bayesian Uncertainty Calibration under
  Covariate Shift

Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift

26 June 2020
Alex J. Chan
Ahmed Alaa
Zhaozhi Qian
M. Schaar
    UQCV
    BDL
    OOD
ArXivPDFHTML

Papers citing "Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift"

10 / 10 papers shown
Title
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization
Behraj Khan
Behroz Mirza
Nouman Durrani
T. Syed
60
0
0
18 Feb 2025
GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction
GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction
Xiayin Lou
Peng Luo
Liqiu Meng
87
0
0
05 Dec 2024
Adversarial Learning Networks: Source-free Unsupervised Domain
  Incremental Learning
Adversarial Learning Networks: Source-free Unsupervised Domain Incremental Learning
Abhinit Kumar Ambastha
Tze-Yun Leong
CLL
OOD
15
1
0
28 Jan 2023
Bayesian Learning for Neural Networks: an algorithmic survey
Bayesian Learning for Neural Networks: an algorithmic survey
M. Magris
Alexandros Iosifidis
BDL
DRL
35
68
0
21 Nov 2022
An Information-theoretical Approach to Semi-supervised Learning under
  Covariate-shift
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift
Gholamali Aminian
Mahed Abroshan
Mohammad Mahdi Khalili
Laura Toni
M. Rodrigues
OOD
18
27
0
24 Feb 2022
Exploring Covariate and Concept Shift for Detection and Calibration of
  Out-of-Distribution Data
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data
Junjiao Tian
Yen-Change Hsu
Yilin Shen
Hongxia Jin
Z. Kira
OODD
19
6
0
28 Oct 2021
When and How Mixup Improves Calibration
When and How Mixup Improves Calibration
Linjun Zhang
Zhun Deng
Kenji Kawaguchi
James Y. Zou
UQCV
20
67
0
11 Feb 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
285
9,136
0
06 Jun 2015
Bayesian Inference with Posterior Regularization and applications to
  Infinite Latent SVMs
Bayesian Inference with Posterior Regularization and applications to Infinite Latent SVMs
Jun Zhu
Ning Chen
Eric P. Xing
BDL
65
157
0
05 Oct 2012
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