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Why ReLU networks yield high-confidence predictions far away from the
  training data and how to mitigate the problem
v1v2 (latest)

Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem

13 December 2018
Matthias Hein
Maksym Andriushchenko
Julian Bitterwolf
    OODD
ArXiv (abs)PDFHTML

Papers citing "Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem"

50 / 366 papers shown
Delving into Out-of-Distribution Detection with Vision-Language
  Representations
Delving into Out-of-Distribution Detection with Vision-Language RepresentationsNeural Information Processing Systems (NeurIPS), 2022
Yifei Ming
Ziyan Cai
Jiuxiang Gu
Yiyou Sun
W. Li
Shouqing Yang
VLMOODD
241
225
0
24 Nov 2022
Promises and Pitfalls of Threshold-based Auto-labeling
Promises and Pitfalls of Threshold-based Auto-labelingNeural Information Processing Systems (NeurIPS), 2022
Harit Vishwakarma
Heguang Lin
Frederic Sala
Ramya Korlakai Vinayak
209
11
0
22 Nov 2022
Are we certain it's anomalous?
Are we certain it's anomalous?
Alessandro Flaborea
Bardh Prenkaj
Bharti Munjal
Marco Aurelio Sterpa
Dario Aragona
L. Podo
Fabio Galasso
363
14
0
16 Nov 2022
Quantifying Model Uncertainty for Semantic Segmentation using Operators
  in the RKHS
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS
Rishabh Singh
José C. Príncipe
UQCV
179
3
0
03 Nov 2022
Watermarking for Out-of-distribution Detection
Watermarking for Out-of-distribution DetectionNeural Information Processing Systems (NeurIPS), 2022
Qizhou Wang
Yifan Zhang
Yonggang Zhang
Jing Zhang
Chen Gong
Tongliang Liu
Bo Han
OODD
169
36
0
27 Oct 2022
On double-descent in uncertainty quantification in overparametrized
  models
On double-descent in uncertainty quantification in overparametrized modelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Lucas Clarté
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
UQCV
443
14
0
23 Oct 2022
Augmentation by Counterfactual Explanation -- Fixing an Overconfident
  Classifier
Augmentation by Counterfactual Explanation -- Fixing an Overconfident ClassifierIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Sumedha Singla
Nihal Murali
Forough Arabshahi
Sofia Triantafyllou
Kayhan Batmanghelich
CML
217
6
0
21 Oct 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the
  Impact of Method & Data Scarcity
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data ScarcityConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Dennis Ulmer
J. Frellsen
Christian Hardmeier
440
27
0
20 Oct 2022
Enhancing Out-of-Distribution Detection in Natural Language
  Understanding via Implicit Layer Ensemble
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer EnsembleConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Hyunsoo Cho
Choonghyun Park
Jaewoo Kang
Kang Min Yoo
Taeuk Kim
Sang-goo Lee
OODD
228
10
0
20 Oct 2022
Packed-Ensembles for Efficient Uncertainty Estimation
Packed-Ensembles for Efficient Uncertainty EstimationInternational Conference on Learning Representations (ICLR), 2022
Olivier Laurent
Adrien Lafage
Enzo Tartaglione
Geoffrey Daniel
Jean-Marc Martinez
Andrei Bursuc
Gianni Franchi
OODD
458
40
0
17 Oct 2022
Prediction Calibration for Generalized Few-shot Semantic Segmentation
Prediction Calibration for Generalized Few-shot Semantic SegmentationIEEE Transactions on Image Processing (IEEE TIP), 2022
Zhihe Lu
Sen He
Da Li
Yi-Zhe Song
Tao Xiang
ViT
130
28
0
15 Oct 2022
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
OpenOOD: Benchmarking Generalized Out-of-Distribution DetectionNeural Information Processing Systems (NeurIPS), 2022
Jingkang Yang
Pengyun Wang
Dejian Zou
Zitang Zhou
Kun Ding
...
Kaiyang Zhou
Wayne Zhang
Dan Hendrycks
Shouqing Yang
Ziwei Liu
OODD
268
316
0
13 Oct 2022
Robust Models are less Over-Confident
Robust Models are less Over-ConfidentNeural Information Processing Systems (NeurIPS), 2022
Julia Grabinski
Paul Gavrikov
J. Keuper
Margret Keuper
AAML
253
31
0
12 Oct 2022
Curved Representation Space of Vision Transformers
Curved Representation Space of Vision TransformersAAAI Conference on Artificial Intelligence (AAAI), 2022
Juyeop Kim
Junha Park
Songkuk Kim
Jongseok Lee
ViT
281
9
0
11 Oct 2022
Boosting Out-of-distribution Detection with Typical Features
Boosting Out-of-distribution Detection with Typical FeaturesNeural Information Processing Systems (NeurIPS), 2022
Yao Zhu
YueFeng Chen
Chuanlong Xie
Xiaodan Li
Rong Zhang
Hui Xue
Xiang Tian
Bolun Zheng
Yao-wu Chen
OODD
277
67
0
09 Oct 2022
To Softmax, or not to Softmax: that is the question when applying Active
  Learning for Transformer Models
To Softmax, or not to Softmax: that is the question when applying Active Learning for Transformer ModelsSymposium on Advances in Databases and Information Systems (ADBIS), 2022
Julius Gonsior
C. Falkenberg
Silvio Magino
Anja Reusch
Maik Thiele
Wolfgang Lehner
UQCV
210
7
0
06 Oct 2022
Two Video Data Sets for Tracking and Retrieval of Out of Distribution
  Objects
Two Video Data Sets for Tracking and Retrieval of Out of Distribution ObjectsAsian Conference on Computer Vision (ACCV), 2022
Kira Maag
Robin Shing Moon Chan
Svenja Uhlemeyer
K. Kowol
Hanno Gottschalk
268
21
0
05 Oct 2022
On Attacking Out-Domain Uncertainty Estimation in Deep Neural Networks
On Attacking Out-Domain Uncertainty Estimation in Deep Neural NetworksInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Huimin Zeng
Zhenrui Yue
Yang Zhang
Ziyi Kou
Lanyu Shang
Dong Wang
OODAAML
167
9
0
03 Oct 2022
Your Out-of-Distribution Detection Method is Not Robust!
Your Out-of-Distribution Detection Method is Not Robust!Neural Information Processing Systems (NeurIPS), 2022
Mohammad Azizmalayeri
Arshia Soltani Moakhar
Arman Zarei
Reihaneh Zohrabi
M. T. Manzuri
M. Rohban
OODD
279
22
0
30 Sep 2022
Out-of-Distribution Detection with Hilbert-Schmidt Independence
  Optimization
Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization
Jingyang Lin
Yu Wang
Qi Cai
Yingwei Pan
Ting Yao
Hongyang Chao
Tao Mei
OODD
137
3
0
26 Sep 2022
Linking Neural Collapse and L2 Normalization with Improved
  Out-of-Distribution Detection in Deep Neural Networks
Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks
J. Haas
William Yolland
B. Rabus
OODD
285
23
0
17 Sep 2022
Towards Improving Calibration in Object Detection Under Domain Shift
Towards Improving Calibration in Object Detection Under Domain ShiftNeural Information Processing Systems (NeurIPS), 2022
Muhammad Akhtar Munir
M. H. Khan
M. Sarfraz
Mohsen Ali
204
27
0
15 Sep 2022
Improving Out-of-Distribution Detection via Epistemic Uncertainty
  Adversarial Training
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training
Derek Everett
A. Nguyen
Luke E. Richards
Edward Raff
OODD
164
4
0
05 Sep 2022
A Principled Evaluation Protocol for Comparative Investigation of the
  Effectiveness of DNN Classification Models on Similar-but-non-identical
  Datasets
A Principled Evaluation Protocol for Comparative Investigation of the Effectiveness of DNN Classification Models on Similar-but-non-identical Datasets
Esla Timothy Anzaku
Haohan Wang
Arnout Van Messem
W. D. Neve
168
2
0
05 Sep 2022
Probing Contextual Diversity for Dense Out-of-Distribution Detection
Probing Contextual Diversity for Dense Out-of-Distribution Detection
Silvio Galesso
M. A. Bravo
Mehdi Naouar
Thomas Brox
200
4
0
30 Aug 2022
Towards In-distribution Compatibility in Out-of-distribution Detection
Towards In-distribution Compatibility in Out-of-distribution Detection
Boxi Wu
Jie Jiang
Haidong Ren
Zifan Du
Wenxiao Wang
Zhifeng Li
Deng Cai
Xiaofei He
Binbin Lin
Wei Liu
OODD
131
1
0
29 Aug 2022
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey
Semi-Supervised and Unsupervised Deep Visual Learning: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Yanbei Chen
Goran Frehse
Xiatian Zhu
Zeynep Akata
331
171
0
24 Aug 2022
Evaluating Out-of-Distribution Detectors Through Adversarial Generation
  of Outliers
Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers
Sangwoong Yoon
Jinwon Choi
Yonghyeon Lee
Yung-Kyun Noh
Frank C. Park
OODD
167
3
0
20 Aug 2022
Uncertainty-guided Source-free Domain Adaptation
Uncertainty-guided Source-free Domain AdaptationEuropean Conference on Computer Vision (ECCV), 2022
Subhankar Roy
Martin Trapp
Andrea Pilzer
Arno Solin
Andrii Zadaianchuk
Elisa Ricci
Arno Solin
EDLTTAUQLMUQCV
257
78
0
16 Aug 2022
Distance-based detection of out-of-distribution silent failures for
  Covid-19 lung lesion segmentation
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation
Jiamin Liang
Yuhao Huang
Haoming Li
Shuangchi He
Xindi Hu
Zejian Chen
Isabel Kaltenborn
Dong Ni
OOD
192
53
0
05 Aug 2022
Approximate Bayesian Neural Operators: Uncertainty Quantification for
  Parametric PDEs
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs
Emilia Magnani
Nicholas Kramer
Runa Eschenhagen
Lorenzo Rosasco
Philipp Hennig
UQCVBDL
190
20
0
02 Aug 2022
Out-of-Distribution Detection with Semantic Mismatch under Masking
Out-of-Distribution Detection with Semantic Mismatch under MaskingEuropean Conference on Computer Vision (ECCV), 2022
Yijun Yang
Ruiyuan Gao
Qiang Xu
OODD
184
37
0
31 Jul 2022
A Novel Data Augmentation Technique for Out-of-Distribution Sample
  Detection using Compounded Corruptions
A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded Corruptions
R. Hebbalaguppe
Soumya Suvra Goshal
Jatin Prakash
H. Khadilkar
Chetan Arora
OODD
201
8
0
28 Jul 2022
Instance-Aware Observer Network for Out-of-Distribution Object
  Segmentation
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation
Victor Besnier
Andrei Bursuc
David Picard
Alexandre Briot
243
1
0
18 Jul 2022
Distance Learner: Incorporating Manifold Prior to Model Training
Distance Learner: Incorporating Manifold Prior to Model Training
Aditya Chetan
Nipun Kwatra
66
1
0
14 Jul 2022
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style
Harnessing Out-Of-Distribution Examples via Augmenting Content and StyleInternational Conference on Learning Representations (ICLR), 2022
Zhuo Huang
Xiaobo Xia
Li Shen
Bo Han
Biwei Huang
Chen Gong
Tongliang Liu
OODD
253
57
0
07 Jul 2022
Partial and Asymmetric Contrastive Learning for Out-of-Distribution
  Detection in Long-Tailed Recognition
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed RecognitionInternational Conference on Machine Learning (ICML), 2022
Haotao Wang
Aston Zhang
Yi Zhu
Shuai Zheng
Mu Li
Alexander J. Smola
Zinan Lin
OODD
401
57
0
04 Jul 2022
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All ClassifierApplied Soft Computing (ASC), 2022
Bartosz Wójcik
J. Grela
Marek Śmieja
Krzysztof Misztal
Jacek Tabor
UQCV
287
4
0
28 Jun 2022
WeShort: Out-of-distribution Detection With Weak Shortcut structure
Jin-Siang Lin
OODD
205
0
0
23 Jun 2022
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD
  Training Data Estimate a Combination of the Same Core Quantities
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core QuantitiesInternational Conference on Machine Learning (ICML), 2022
Julian Bitterwolf
Alexander Meinke
Maximilian Augustin
Matthias Hein
OODD
206
32
0
20 Jun 2022
Supervision Adaptation Balancing In-distribution Generalization and
  Out-of-distribution Detection
Supervision Adaptation Balancing In-distribution Generalization and Out-of-distribution DetectionIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Zhilin Zhao
LongBing Cao
Kun-Yu Lin
223
7
0
19 Jun 2022
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing
  Long-tailed datasets
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasetsInternational Conference on Machine Learning (ICML), 2022
Jianguo Huang
Lue Tao
Renchunzi Xie
Lei Feng
Bo An
OODD
297
44
0
17 Jun 2022
READ: Aggregating Reconstruction Error into Out-of-distribution
  Detection
READ: Aggregating Reconstruction Error into Out-of-distribution DetectionAAAI Conference on Artificial Intelligence (AAAI), 2022
Wenyu Jiang
Yuxin Ge
Hao Cheng
Mingcai Chen
Shuai Feng
Chongjun Wang
OODD
299
14
0
15 Jun 2022
Confidence Score for Source-Free Unsupervised Domain Adaptation
Confidence Score for Source-Free Unsupervised Domain AdaptationInternational Conference on Machine Learning (ICML), 2022
Jonghyun Lee
Dahuin Jung
Junho Yim
Sung-Hoon Yoon
TTA
209
90
0
14 Jun 2022
EnergyMatch: Energy-based Pseudo-Labeling for Semi-Supervised Learning
EnergyMatch: Energy-based Pseudo-Labeling for Semi-Supervised Learning
Xiaohua Xie
Yin Li
Yong Jae Lee
92
1
0
13 Jun 2022
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement
  Learning
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning
Bertrand Charpentier
Ransalu Senanayake
Mykel Kochenderfer
Stephan Günnemann
PERUD
197
30
0
03 Jun 2022
HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System
HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence SystemInternational Conference on Neural Information Processing (ICONIP), 2022
Bao-Sinh Nguyen
Q. Tran
Tuan-Anh Dang Nguyen
D. Nguyen
H. Le
138
1
0
01 Jun 2022
Exact Feature Collisions in Neural Networks
Exact Feature Collisions in Neural Networks
Utku Ozbulak
Manvel Gasparyan
Shodhan Rao
W. D. Neve
Arnout Van Messem
AAML
137
1
0
31 May 2022
How Useful are Gradients for OOD Detection Really?
How Useful are Gradients for OOD Detection Really?
Conor Igoe
Youngseog Chung
I. Char
J. Schneider
OODD
172
27
0
20 May 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural
  Networks
Posterior Refinement Improves Sample Efficiency in Bayesian Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Agustinus Kristiadi
Runa Eschenhagen
Philipp Hennig
BDL
218
15
0
20 May 2022
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