Towards neural networks that provably know when they don't know

26 September 2019

Matthias Hein

Papers citing "Towards neural networks that provably know when they don't know"

50 / 91 papers shown

Title
Open-set Anomaly Segmentation in Complex Scenarios Song Xia Yi Yu Henghui Ding Wenhan Yang S. Liu Alex C. Kot Xudong Jiang DiffM 50 0 0 28 Apr 2025
Look Around and Find Out: OOD Detection with Relative Angles Berker Demirel Marco Fumero Francesco Locatello 29 0 0 06 Oct 2024
Forte : Finding Outliers with Representation Typicality Estimation Debargha Ganguly Warren Morningstar A. Yu Vipin Chaudhary OODD 39 0 0 02 Oct 2024
Your Classifier Can Be Secretly a Likelihood-Based OOD Detector Jirayu Burapacheep Yixuan Li OODD 32 3 0 09 Aug 2024
When and How Does In-Distribution Label Help Out-of-Distribution Detection? Xuefeng Du Yiyou Sun Yixuan Li 27 7 0 28 May 2024
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning Jie Chen Pengfei Ou Yuxin Chang Hengrui Zhang Xiao-Yan Li E. H. Sargent Wei Chen 30 0 0 18 Apr 2024
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey Naveen Karunanayake Ravin Gunawardena Suranga Seneviratne Sanjay Chawla OOD 38 5 0 08 Apr 2024
Hyperbolic Metric Learning for Visual Outlier Detection Alvaro Gonzalez-Jimenez Simone Lionetti Dena Bazazian Philippe Gottfrois Fabian Gröger M. Pouly A. Navarini 51 1 0 22 Mar 2024
How Does Unlabeled Data Provably Help Out-of-Distribution Detection? Xuefeng Du Zhen Fang Ilias Diakonikolas Yixuan Li OODD 41 27 0 05 Feb 2024
How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection? Soumya Suvra Ghosal Yiyou Sun Yixuan Li OODD 22 10 0 22 Dec 2023
EAT: Towards Long-Tailed Out-of-Distribution Detection Tong Wei Bo-Lin Wang Min-Ling Zhang OODD 18 14 0 14 Dec 2023
ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection Yichen Bai Zongbo Han Changqing Zhang Bing Cao Xiaoheng Jiang Qinghua Hu OODD 41 18 0 26 Nov 2023
RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-distribution Detection Yue Song N. Sebe Wei Wang OODD 24 1 0 23 Nov 2023
Incremental Object-Based Novelty Detection with Feedback Loop Simone Caldarella Elisa Ricci Rahaf Aljundi 26 0 0 15 Nov 2023
Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks Ahmad Rashid Serena Hacker Guojun Zhang Agustinus Kristiadi Pascal Poupart OODD 23 0 0 07 Nov 2023
Dream the Impossible: Outlier Imagination with Diffusion Models Xuefeng Du Yiyou Sun Xiaojin Zhu Yixuan Li 20 53 0 23 Sep 2023
Provable Dynamic Fusion for Low-Quality Multimodal Data Qingyang Zhang Haitao Wu Changqing Zhang Qinghua Hu H. Fu Joey Tianyi Zhou Xi Peng 34 55 0 03 Jun 2023
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection Wenyu Jiang Hao Cheng Mingcai Chen Chongjun Wang Hongxin Wei OOD OODD 24 9 0 03 Jun 2023
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection Nicola Franco Daniel Korth J. Lorenz Karsten Roscher Stephan Guennemann 26 5 0 27 Mar 2023
AUTO: Adaptive Outlier Optimization for Online Test-Time OOD Detection Puning Yang Jian Liang Jie Cao R. He 27 12 0 22 Mar 2023
Non-Parametric Outlier Synthesis Leitian Tao Xuefeng Du Xiaojin Zhu Yixuan Li OODD 17 98 0 06 Mar 2023
DeepLens: Interactive Out-of-distribution Data Detection in NLP Models D. Song Zhijie Wang Yuheng Huang Lei Ma Tianyi Zhang 16 4 0 02 Mar 2023
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts H. Bui Anqi Liu OOD UQCV 11 6 0 13 Feb 2023
Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects Kira Maag Robin Shing Moon Chan Svenja Uhlemeyer K. Kowol Hanno Gottschalk 30 19 0 05 Oct 2022
On Attacking Out-Domain Uncertainty Estimation in Deep Neural Networks Huimin Zeng Zhenrui Yue Yang Zhang Ziyi Kou Lanyu Shang Dong Wang OOD AAML 27 7 0 03 Oct 2022
Understanding Open-Set Recognition by Jacobian Norm and Inter-Class Separation Jaewoo Park Hojin Park Eunju Jeong Andrew Beng Jin Teoh 19 5 0 23 Sep 2022
Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers Sangwoong Yoon Jinwon Choi Yonghyeon Lee Yung-Kyun Noh Frank C. Park OODD 13 1 0 20 Aug 2022
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition Haotao Wang Aston Zhang Yi Zhu Shuai Zheng Mu Li Alexander J. Smola Zhangyang Wang OODD 138 48 0 04 Jul 2022
POEM: Out-of-Distribution Detection with Posterior Sampling Yifei Ming Ying Fan Yixuan Li OODD 25 113 0 28 Jun 2022
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities Julian Bitterwolf Alexander Meinke Maximilian Augustin Matthias Hein OODD 13 25 0 20 Jun 2022
Test-Time Adaptation for Visual Document Understanding Sayna Ebrahimi Sercan Ö. Arik Tomas Pfister OOD 31 6 0 15 Jun 2022
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning Bertrand Charpentier Ransalu Senanayake Mykel Kochenderfer Stephan Günnemann PER UD 45 24 0 03 Jun 2022
Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning Julian Burghoff Robin Shing Moon Chan Hanno Gottschalk Annika Muetze Tobias Riedlinger Matthias Rottmann Marius Schubert BDL 21 0 0 30 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 16 48 0 01 May 2022
Out-of-Distribution Detection with Deep Nearest Neighbors Yiyou Sun Yifei Ming Xiaojin Zhu Yixuan Li OODD 19 487 0 13 Apr 2022
Accelerated Design and Deployment of Low-Carbon Concrete for Data Centers Xiou Ge Richard Goodwin Haizi Yu Pablo Romero Omar Abdelrahman Amruta Sudhalkar Julius Kusuma Ryan Cialdella Nakul Garg L. Varshney 17 10 0 11 Apr 2022
Detecting and Learning the Unknown in Semantic Segmentation Robin Shing Moon Chan Svenja Uhlemeyer Matthias Rottmann Hanno Gottschalk UQCV 17 5 0 17 Feb 2022
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning A. Feder Cooper Emanuel Moss Benjamin Laufer Helen Nissenbaum MLAU 24 85 0 10 Feb 2022
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training Shiwei Liu Tianlong Chen Xiaohan Chen Li Shen D. Mocanu Zhangyang Wang Mykola Pechenizkiy 11 106 0 05 Feb 2022
Explanatory Learning: Beyond Empiricism in Neural Networks Antonio Norelli Giorgio Mariani Luca Moschella Andrea Santilli Giambattista Parascandolo Simone Melzi Emanuele Rodolà 14 2 0 25 Jan 2022
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection R. Kaur Susmit Jha Anirban Roy Sangdon Park Edgar Dobriban O. Sokolsky Insup Lee OODD 12 45 0 07 Jan 2022
DICE: Leveraging Sparsification for Out-of-Distribution Detection Yiyou Sun Yixuan Li OODD 30 151 0 18 Nov 2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness Jongheon Jeong Sejun Park Minkyu Kim Heung-Chang Lee Do-Guk Kim Jinwoo Shin AAML 15 55 0 17 Nov 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 28 80 0 26 Oct 2021
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 173 875 0 21 Oct 2021
DOODLER: Determining Out-Of-Distribution Likelihood from Encoder Reconstructions Jonathan S. Kent Bo-wen Li OODD 13 0 0 27 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 30 16 0 20 Sep 2021
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue Keke Tang Dingruibo Miao Weilong Peng Jianpeng Wu Yawen Shi Zhaoquan Gu Zhihong Tian Wenping Wang OODD 135 30 0 13 Aug 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 17 65 0 26 Jul 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 27 21 0 20 Jul 2021