Learning Confidence for Out-of-Distribution Detection in Neural Networks

13 February 2018

Papers citing "Learning Confidence for Out-of-Distribution Detection in Neural Networks"

50 / 114 papers shown

Title
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 188 879 0 21 Oct 2021
A novel network training approach for open set image recognition Md Tahmid Hossaina S. Teng Guojun Lu Ferdous Sohel 26 0 0 27 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 38 16 0 20 Sep 2021
Efficient Out-of-Distribution Detection Using Latent Space of $β$ -VAE for Cyber-Physical Systems Shreyas Ramakrishna Zahra Rahiminasab G. Karsai Arvind Easwaran Abhishek Dubey OODD 19 27 0 26 Aug 2021
Out-of-Distribution Detection Using Outlier Detection Methods Jan Diers Christian Pigorsch OODD 24 3 0 18 Aug 2021
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation Victor Besnier Andrei Bursuc David Picard Alexandre Briot UQCV 24 48 0 03 Aug 2021
Towards Consistent Predictive Confidence through Fitted Ensembles Navid Kardan Ankit Sharma Kenneth O. Stanley FedML OODD 16 8 0 22 Jun 2021
Robust Out-of-Distribution Detection on Deep Probabilistic Generative Models Jaemoo Choi Changyeon Yoon Jeongwoo Bae Myung-joo Kang OODD 30 4 0 15 Jun 2021
InFlow: Robust outlier detection utilizing Normalizing Flows Nishant Kumar Pia Hanfeld Michael Hecht Michael Bussmann Stefan Gumhold Nico Hoffmann OODD OOD TPM 29 4 0 10 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 Jun 2021
OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers Kuniaki Saito Donghyun Kim Kate Saenko 34 63 0 28 May 2021
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs Théo Lacombe Yuichi Ike Mathieu Carrière Frédéric Chazal Marc Glisse Yuhei Umeda 29 20 0 07 May 2021
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation Robin Shing Moon Chan Krzysztof Lis Svenja Uhlemeyer Hermann Blum S. Honari Roland Siegwart Pascal Fua Mathieu Salzmann Matthias Rottmann UQCV 24 136 0 30 Apr 2021
MOOD: Multi-level Out-of-distribution Detection Ziqian Lin Sreya . Dutta Roy Yixuan Li OODD 34 114 0 30 Apr 2021
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems Shohei Enomoto Takeharu Eda UQCV 46 17 0 15 Apr 2021
Unsupervised Class-Incremental Learning Through Confusion Shivam Khare Kun Cao James M. Rehg SSL CLL 24 6 0 09 Apr 2021
Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications Lixuan Yang A. Finamore Feng Jun Dario Rossi 19 47 0 07 Apr 2021
SSD: A Unified Framework for Self-Supervised Outlier Detection Vikash Sehwag M. Chiang Prateek Mittal OODD 31 330 0 22 Mar 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip Torr Y. Gal UD UQCV PER BDL 29 145 0 23 Feb 2021
Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approaches Jasmin Breitenstein Jan-Aike Termöhlen Daniel Lipinski Tim Fingscheidt AAML 22 35 0 11 Feb 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation Alexandre Ramé Matthieu Cord FedML 50 51 0 14 Jan 2021
Bridging In- and Out-of-distribution Samples for Their Better Discriminability Engkarat Techapanurak Anh-Chuong Dang Takayuki Okatani OODD 25 3 0 07 Jan 2021
Confidence Estimation via Auxiliary Models Charles Corbière Nicolas Thome A. Saporta Tuan-Hung Vu Matthieu Cord P. Pérez TPM 29 47 0 11 Dec 2020
Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation Robin Shing Moon Chan Matthias Rottmann Hanno Gottschalk OODD 37 149 0 09 Dec 2020
Out-of-Distribution Detection for Automotive Perception Julia Nitsch Masha Itkina Ransalu Senanayake Juan I. Nieto M. Schmidt Roland Siegwart Mykel J. Kochenderfer Cesar Cadena UQCV 20 63 0 03 Nov 2020
Multiscale Score Matching for Out-of-Distribution Detection Ahsan Mahmood Junier Oliva M. Styner OODD 22 30 0 25 Oct 2020
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference Jianguo Zhang Kazuma Hashimoto Wenhao Liu Chien-Sheng Wu Yao Wan Philip S. Yu R. Socher Caiming Xiong 14 92 0 25 Oct 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 89 1,292 0 08 Oct 2020
Toward Reliable Models for Authenticating Multimedia Content: Detecting Resampling Artifacts With Bayesian Neural Networks Anatol Maier Benedikt Lorch Christian Riess AAML 38 17 0 28 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 50 0 16 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 19 234 0 10 Jul 2020
Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation Ertunc Erdil K. Chaitanya Neerav Karani E. Konukoglu OODD 24 7 0 18 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES) Andrew Critch David M. Krueger 30 50 0 30 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 Z. Abdallah 21 4 0 08 Apr 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 21 6 0 28 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 24 115 0 13 Feb 2020
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems Feiyang Cai X. Koutsoukos OODD 121 73 0 28 Jan 2020
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation Alireza Mehrtash W. Wells C. Tempany Purang Abolmaesumi Tina Kapur OOD FedML UQCV 24 264 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 17 455 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 35 52 0 18 Nov 2019
Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method Vishwanath A. Sindagi R. Yasarla Vishal M. Patel 21 87 0 28 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 24 45 0 23 Oct 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 87 1,353 0 21 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 21 83 0 09 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 27 282 0 01 Oct 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 27 139 0 26 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 25 121 0 09 Sep 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 11 38 0 20 Aug 2019
Entropic Out-of-Distribution Detection David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD UQCV 22 31 0 15 Aug 2019