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"

6 / 6 papers shown

Title
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data Jiaxing Huang Dayan Guan Aoran Xiao Shijian Lu 126 210 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 194 501 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 128 249 0 14 Dec 2020
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation Zhedong Zheng Yi Yang NoLa 164 494 0 08 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 234 11,568 0 09 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 243 9,042 0 06 Jun 2015