Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised
Domain Generalization

Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization

25 January 2024

Muhammad Haris Khan

Papers citing "Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization"

5 / 5 papers shown

Title
TactileNet: Bridging the Accessibility Gap with AI-Generated Tactile Graphics for Individuals with Vision Impairment Adnan Khan Alireza Choubineh Mai A. Shaaban Abbas Akkasi Majid Komeili DiffM 35 0 0 07 Apr 2025
SelfReg: Self-supervised Contrastive Regularization for Domain Generalization Daehee Kim Seunghyun Park Jinkyu Kim Jaekoo Lee OOD SSL 62 264 0 20 Apr 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 209 508 0 15 Jan 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,134 0 06 Jun 2015