A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded Corruptions

28 July 2022

Papers citing "A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded Corruptions"

6 / 6 papers shown

Title
VOS: Learning What You Don't Know by Virtual Outlier Synthesis Xuefeng Du Zhaoning Wang Mu Cai Yixuan Li OODD 174 220 0 02 Feb 2022
On the Importance of Gradients for Detecting Distributional Shifts in the Wild Rui Huang Andrew Geng Yixuan Li 175 328 0 01 Oct 2021
Deep Domain-Adversarial Image Generation for Domain Generalisation Kaiyang Zhou Yongxin Yang Timothy M. Hospedales Tao Xiang OOD 204 404 0 12 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,356 0 25 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 261 9,134 0 06 Jun 2015