Confidence estimation in Deep Neural networks via density modelling

21 July 2017

Papers citing "Confidence estimation in Deep Neural networks via density modelling"

10 / 10 papers shown

Title
Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Design Yingrui Ji Yao Zhu Zhigang Li Jiansheng Chen Yun-long Kong Jingbo Chen OODD 43 0 0 06 Mar 2024
Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier Sumedha Singla Nihal Murali Forough Arabshahi Sofia Triantafyllou Kayhan Batmanghelich CML 59 5 0 21 Oct 2022
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space Rui Huang Yixuan Li OODD 39 237 0 05 May 2021
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 110 1,306 0 08 Oct 2020
Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples Alejandro Barredo Arrieta Javier Del Ser AAML 15 22 0 25 Mar 2020
Entropic Out-of-Distribution Detection David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD UQCV 25 32 0 15 Aug 2019
Input Prioritization for Testing Neural Networks Taejoon Byun Vaibhav Sharma Abhishek Vijayakumar Sanjai Rayadurgam D. Cofer AAML 29 67 0 11 Jan 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 31 1,457 0 11 Dec 2018
Classification Uncertainty of Deep Neural Networks Based on Gradient Information Philipp Oberdiek Matthias Rottmann Hanno Gottschalk UQCV 17 64 0 22 May 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015