Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples

26 November 2017

Papers citing "Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples"

36 / 186 papers shown

Title
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation Alireza Mehrtash W. Wells C. Tempany Purang Abolmaesumi Tina Kapur OOD FedML UQCV 24 262 0 29 Nov 2019
Scaling Out-of-Distribution Detection for Real-World Settings Dan Hendrycks Steven Basart Mantas Mazeika Andy Zou Joe Kwon Mohammadreza Mostajabi Jacob Steinhardt D. Song OODD 15 455 0 25 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 33 52 0 18 Nov 2019
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning J. Liu John Paisley M. Kioumourtzoglou B. Coull UQCV UD PER 27 83 0 11 Nov 2019
Identifying Unknown Instances for Autonomous Driving K. Wong Shenlong Wang Mengye Ren Ming Liang R. Urtasun 22 110 0 24 Oct 2019
Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output Vahdat Abdelzad Krzysztof Czarnecki Rick Salay Taylor Denouden Sachin Vernekar Buu Phan OODD 19 45 0 23 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 19 83 0 09 Oct 2019
Open Set Medical Diagnosis Viraj Prabhu A. Kannan Geoffrey Tso Namit Katariya Manish Chablani David Sontag X. Amatriain 21 9 0 07 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 27 281 0 01 Oct 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 22 139 0 26 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 18 121 0 09 Sep 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 11 37 0 20 Aug 2019
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy Qing Yu Kiyoharu Aizawa OODD 11 163 0 14 Aug 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 62 1,422 0 16 Jul 2019
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data Simao Eduardo A. Nazábal Christopher K. I. Williams Charles Sutton DRL 11 32 0 15 Jul 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 18 716 0 07 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 56 240 0 06 Jun 2019
Training Data Subset Search with Ensemble Active Learning Kashyap Chitta J. Álvarez Elmar Haussmann C. Farabet 17 13 0 29 May 2019
Analysis of Confident-Classifiers for Out-of-distribution Detection Sachin Vernekar Ashish Gaurav Taylor Denouden Buu Phan Vahdat Abdelzad Rick Salay Krzysztof Czarnecki OODD 18 18 0 27 Apr 2019
Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition Devraj Mandal Sanath Narayan Sai Kumar Dwivedi Vikram Gupta Shuaib Ahmed F. Khan Ling Shao OODD 14 141 0 18 Apr 2019
Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild Kibok Lee Kimin Lee Jinwoo Shin Honglak Lee CLL 29 201 0 29 Mar 2019
Deep CNN-based Multi-task Learning for Open-Set Recognition Poojan Oza Vishal M. Patel 16 35 0 07 Mar 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 19 20 0 28 Feb 2019
The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning Benjamin J. Meyer Tom Drummond 14 33 0 27 Feb 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 17 717 0 28 Jan 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 40 552 0 13 Dec 2018
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 31 1,449 0 11 Dec 2018
Building robust classifiers through generation of confident out of distribution examples K. Sricharan Ashok Srivastava OOD 8 31 0 01 Dec 2018
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 27 357 0 29 Oct 2018
Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers Apoorv Vyas Nataraj Jammalamadaka Xia Zhu Dipankar Das Bharat Kaul Theodore L. Willke OODD 16 246 0 04 Sep 2018
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection Mahdieh Abbasi Arezoo Rajabi A. Mozafari R. Bobba Christian Gagné AAML 21 9 0 21 Aug 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 21 1,994 0 10 Jul 2018
Hierarchical Novelty Detection for Visual Object Recognition Kibok Lee Kimin Lee Kyle Min Y. Zhang Jinwoo Shin Honglak Lee BDL 44 67 0 02 Apr 2018
Learning Confidence for Out-of-Distribution Detection in Neural Networks Terrance Devries Graham W. Taylor OOD OODD 17 581 0 13 Feb 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012