Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

8 June 2017

Papers citing "Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks"

50 / 481 papers shown

Title
Unsupervised Domain Adaptation in the Absence of Source Data Roshni Sahoo Divya Shanmugam John Guttag OOD 22 18 0 20 Jul 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances Jihoon Tack Sangwoo Mo Jongheon Jeong Jinwoo Shin OODD 11 589 0 16 Jul 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation Xuming Ran Mingkun Xu Lingrui Mei Qi Xu Quanying Liu OODD UQCV 42 51 0 16 Jul 2020
Improving Face Recognition by Clustering Unlabeled Faces in the Wild Aruni RoyChowdhury Xiang Yu Kihyuk Sohn Erik Learned-Miller Manmohan Chandraker CVBM 25 19 0 14 Jul 2020
Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner Eugene Lee E. Chen Chen-Yi Lee 26 159 0 14 Jul 2020
Contrastive Training for Improved Out-of-Distribution Detection Jim Winkens Rudy Bunel Abhijit Guha Roy Robert Stanforth Vivek Natarajan ... Alan Karthikesalingam Simon A. A. Kohl taylan. cemgil S. M. Ali Eslami Olaf Ronneberger OODD 19 236 0 10 Jul 2020
Boundary thickness and robustness in learning models Yaoqing Yang Rekha Khanna Yaodong Yu A. Gholami Kurt Keutzer Joseph E. Gonzalez Kannan Ramchandran Michael W. Mahoney OOD 18 37 0 09 Jul 2020
A Critical Evaluation of Open-World Machine Learning Liwei Song Vikash Sehwag A. Bhagoji Prateek Mittal AAML 24 8 0 08 Jul 2020
A Benchmark of Medical Out of Distribution Detection Tianshi Cao Chinwei Huang D. Y. Hui Joseph Paul Cohen OOD 32 58 0 08 Jul 2020
Confidence-Aware Learning for Deep Neural Networks J. Moon Jihyo Kim Younghak Shin Sangheum Hwang UQCV 28 144 0 03 Jul 2020
Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation Ertunc Erdil K. Chaitanya Neerav Karani E. Konukoglu OODD 27 7 0 18 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 24 84 0 16 Jun 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets Zhihui Shao Jianyi Yang Shaolei Ren OODD 35 11 0 16 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 17 7 0 15 Jun 2020
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures Saul Calderon-Ramirez Luis Oala J. Torrents-Barrena Shengxiang-Yang Armaghan Moemeni Wojciech Samek Miguel A. Molina-Cabello 33 10 0 14 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES) Andrew Critch David M. Krueger 30 50 0 30 May 2020
Few-Shot Open-Set Recognition using Meta-Learning Bo Liu Hao Kang Haoxiang Li G. Hua Nuno Vasconcelos BDL EDL 28 89 0 27 May 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 30 81 0 16 Apr 2020
DeepStreamCE: A Streaming Approach to Concept Evolution Detection in Deep Neural Networks Lorraine Chambers M. Gaber Zahraa S Abdallah 21 4 0 08 Apr 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 248 290 0 17 Mar 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Yue Liu P. Varshney D. Song AAML 28 47 0 16 Mar 2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods Sanghyuk Chun Seong Joon Oh Sangdoo Yun Dongyoon Han Junsuk Choe Y. Yoo AAML OOD 345 53 0 09 Mar 2020
A Post-processing Method for Detecting Unknown Intent of Dialogue System via Pre-trained Deep Neural Network Classifier Ting-En Lin Hua Xu 47 31 0 07 Mar 2020
Unbiased Mean Teacher for Cross-domain Object Detection Jinhong Deng Wen Li Yuhua Chen Lixin Duan 79 287 0 02 Mar 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 Feb 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 24 561 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 38 277 0 24 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 29 116 0 13 Feb 2020
Semi-Supervised Class Discovery Jeremy Nixon J. Liu David Berthelot 20 2 0 10 Feb 2020
OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples Changjian Chen Jun Yuan Yafeng Lu Yang Liu Hang Su Songtao Yuan Shixia Liu OODD 26 63 0 08 Feb 2020
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems Feiyang Cai X. Koutsoukos OODD 123 75 0 28 Jan 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn David Berthelot Chun-Liang Li Zizhao Zhang Nicholas Carlini E. D. Cubuk Alexey Kurakin Han Zhang Colin Raffel AAML 104 3,479 0 21 Jan 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 21 25 0 31 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 43 529 0 06 Dec 2019
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation Alireza Mehrtash W. Wells C. Tempany Purang Abolmaesumi Tina Kapur OOD FedML UQCV 24 265 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 20 463 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 38 52 0 18 Nov 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 89 1,359 0 21 Oct 2019
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
Open Set Medical Diagnosis Viraj Prabhu A. Kannan Geoffrey Tso Namit Katariya Manish Chablani David Sontag X. Amatriain 23 9 0 07 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
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
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
Metamorphic Testing of a Deep Learning based Forecaster Anurag Dwarakanath Manish Ahuja Sanjay Podder Silja Vinu Arijit Naskar M. Koushik AI4TS 16 9 0 13 Jul 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 38 77 0 19 Jun 2019