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Uncertainty-Induced Transferability Representation for Source-Free
  Unsupervised Domain Adaptation

Uncertainty-Induced Transferability Representation for Source-Free Unsupervised Domain Adaptation

30 August 2022
Jiangbo Pei
Zhuqing Jiang
Aidong Men
Liang Chen
Yang Liu
Qingchao Chen
ArXivPDFHTML

Papers citing "Uncertainty-Induced Transferability Representation for Source-Free Unsupervised Domain Adaptation"

9 / 9 papers shown
Title
A Comprehensive Survey on Source-free Domain Adaptation
A Comprehensive Survey on Source-free Domain Adaptation
Zhiqi Yu
Jingjing Li
Zhekai Du
Lei Zhu
H. Shen
TTA
29
94
0
23 Feb 2023
A Multi-stage Framework with Mean Subspace Computation and Recursive
  Feedback for Online Unsupervised Domain Adaptation
A Multi-stage Framework with Mean Subspace Computation and Recursive Feedback for Online Unsupervised Domain Adaptation
Ji-Sun Moon
Debasmit Das
C. S. George Lee
27
6
0
24 Jun 2022
Model Adaptation: Historical Contrastive Learning for Unsupervised
  Domain Adaptation without Source Data
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data
Jiaxing Huang
Dayan Guan
Aoran Xiao
Shijian Lu
153
212
0
07 Oct 2021
Source-Free Domain Adaptation for Image Segmentation
Source-Free Domain Adaptation for Image Segmentation
M. Bateson
H. Kervadec
Jose Dolz
H. Lombaert
Ismail Ben Ayed
OOD
MedIm
129
65
0
06 Aug 2021
Domain Impression: A Source Data Free Domain Adaptation Method
Domain Impression: A Source Data Free Domain Adaptation Method
V. Kurmi
Venkatesh Subramanian
Vinay P. Namboodiri
TTA
151
150
0
17 Feb 2021
Casting a BAIT for Offline and Online Source-free Domain Adaptation
Casting a BAIT for Offline and Online Source-free Domain Adaptation
Shiqi Yang
Yaxing Wang
Joost van de Weijer
Luis Herranz
Shangling Jui
TTA
91
45
0
23 Oct 2020
Transferability and Hardness of Supervised Classification Tasks
Transferability and Hardness of Supervised Classification Tasks
Anh Tran
Cuong V Nguyen
Tal Hassner
134
164
0
21 Aug 2019
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
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