Augmentation by Counterfactual Explanation -- Fixing an Overconfident
Classifier

Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier

21 October 2022

Forough Arabshahi

Sofia Triantafyllou

Kayhan Batmanghelich

Papers citing "Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier"

7 / 7 papers shown

Title
Accurate Explanation Model for Image Classifiers using Class Association Embedding Ruitao Xie Jingbang Chen Limai Jiang Rui Xiao Yi-Lun Pan Yunpeng Cai 71 4 0 31 Dec 2024
On the Importance of Gradients for Detecting Distributional Shifts in the Wild Rui Huang Andrew Geng Yixuan Li 195 328 0 01 Oct 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 65 100 0 11 Jan 2021
Improving model calibration with accuracy versus uncertainty optimization R. Krishnan Omesh Tickoo UQCV 188 157 0 14 Dec 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 258 36,371 0 25 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015