A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

7 October 2016

Papers citing "A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks"

50 / 770 papers shown

Title
Extraction of Complex DNN Models: Real Threat or Boogeyman? B. Atli S. Szyller Mika Juuti Samuel Marchal Nadarajah Asokan MLAU MIACV 33 45 0 11 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 27 83 0 09 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 33 283 0 01 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 27 92 0 29 Sep 2019
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate Lu Mi Hao Wang Yonglong Tian Hao He Nir Shavit UQCV 26 30 0 28 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 33 139 0 26 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 28 121 0 09 Sep 2019
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction Stefan Larson Anish Mahendran Joseph Peper Christopher Clarke Andrew Lee ... Jonathan K. Kummerfeld Kevin Leach M. Laurenzano Lingjia Tang Jason Mars 11 515 0 04 Sep 2019
Active Learning for UAV-based Semantic Mapping Hermann Blum Silvan Rohrbach Marija Popović Luca Bartolomei Roland Siegwart 14 9 0 29 Aug 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 16 38 0 20 Aug 2019
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
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy Qing Yu Kiyoharu Aizawa OODD 19 164 0 14 Aug 2019
SpanBERT: Improving Pre-training by Representing and Predicting Spans Mandar Joshi Danqi Chen Yinhan Liu Daniel S. Weld Luke Zettlemoyer Omer Levy 60 1,945 0 24 Jul 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 106 1,428 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 19 32 0 15 Jul 2019
FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis E. Çallı K. Murphy Ecem Sogancioglu Bram van Ginneken MedIm OOD 14 15 0 02 Jul 2019
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks Aryan Mobiny H. Nguyen S. Moulik Naveen Garg Carol C. Wu UQCV BDL 20 155 0 07 Jun 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 50 717 0 07 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 80 1,662 0 06 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 56 241 0 06 Jun 2019
Robot-Assisted Feeding: Generalizing Skewering Strategies across Food Items on a Realistic Plate Ryan Feng Youngsun Kim Gilwoo Lee E. Gordon Matt Schmittle Shivaum Kumar Tapomayukh Bhattacharjee S. Srinivasa 16 22 0 05 Jun 2019
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections R. Y. Rohekar Yaniv Gurwicz Shami Nisimov Gal Novik BDL UQCV 26 13 0 30 May 2019
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT Philipp Seeböck J. Orlando T. Schlegl S. Waldstein Hrvoje Bogunović S. Klimscha Georg Langs U. Schmidt-Erfurth UQCV 22 134 0 29 May 2019
Combating Label Noise in Deep Learning Using Abstention S. Thulasidasan Tanmoy Bhattacharya J. Bilmes Gopinath Chennupati J. Mohd-Yusof NoLa 22 178 0 27 May 2019
Detecting Adversarial Examples and Other Misclassifications in Neural Networks by Introspection Jonathan Aigrain Marcin Detyniecki AAML 27 30 0 22 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 25 12 0 19 May 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 403 4,694 0 13 May 2019
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark Gales UQCV 27 232 0 30 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 19 35 0 12 Apr 2019
Large-Scale Long-Tailed Recognition in an Open World Ziwei Liu Zhongqi Miao Xiaohang Zhan Jiayun Wang Boqing Gong Stella X. Yu 48 1,137 0 10 Apr 2019
Deep CNN-based Multi-task Learning for Open-Set Recognition Poojan Oza Vishal M. Patel 24 35 0 07 Mar 2019
Prostate Segmentation from 3D MRI Using a Two-Stage Model and Variable-Input Based Uncertainty Measure Huitong Pan Brandon Yushan Feng Quan Chen C. Meyer Xue Feng 24 16 0 06 Mar 2019
Calibration of Encoder Decoder Models for Neural Machine Translation Aviral Kumar Sunita Sarawagi 27 98 0 03 Mar 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 24 122 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 34 721 0 28 Jan 2019
A witness function based construction of discriminative models using Hermite polynomials H. Mhaskar A. Cloninger Xiuyuan Cheng 24 9 0 10 Jan 2019
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien UQCV 30 24 0 08 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam Suchi Saria OOD 27 103 0 02 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 55 554 0 13 Dec 2018
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 31 1,457 0 11 Dec 2018
Building robust classifiers through generation of confident out of distribution examples K. Sricharan Ashok Srivastava OOD 18 31 0 01 Dec 2018
Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects Michael A. Alcorn Melvin Johnson Zhitao Gong Chengfei Wang Long Mai Naveen Ari Stella Laurenzo 47 299 0 28 Nov 2018
Probabilistic Object Detection: Definition and Evaluation David Hall Feras Dayoub John Skinner Haoyang Zhang Dimity Miller Peter Corke G. Carneiro A. Angelova Niko Sünderhauf UQCV 38 111 0 27 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 397 0 19 Nov 2018
Deep Weighted Averaging Classifiers Dallas Card Michael J.Q. Zhang Hao Tang 22 41 0 06 Nov 2018
Single-Model Uncertainties for Deep Learning Natasa Tagasovska David Lopez-Paz UQCV BDL 36 25 0 02 Nov 2018
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 33 361 0 29 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 20 82 0 02 Oct 2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection Dimity Miller Feras Dayoub Michael Milford Niko Sünderhauf 23 105 0 17 Sep 2018