Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data

14 July 2021

Papers citing "Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data"

7 / 7 papers shown

Title
A Comprehensive Survey on Source-free Domain Adaptation Zhiqi Yu Jingjing Li Zhekai Du Lei Zhu H. Shen TTA 23 94 0 23 Feb 2023
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
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Y. S. Rawat M. Shah 220 508 0 15 Jan 2021
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer Jian Liang Dapeng Hu Yunbo Wang R. He Jiashi Feng 145 250 0 14 Dec 2020
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation Zhedong Zheng Yi Yang NoLa 188 497 0 08 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,681 0 09 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015