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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 / 349 papers shown
Title
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
Julian Bitterwolf
Maximilian Müller
Matthias Hein
OODD
104
92
0
01 Jun 2023
Towards Semi-supervised Universal Graph Classification
Towards Semi-supervised Universal Graph Classification
Xiao Luo
Yusheng Zhao
Yifang Qin
Wei Ju
Ming Zhang
89
33
0
31 May 2023
Perception and Semantic Aware Regularization for Sequential Confidence
  Calibration
Perception and Semantic Aware Regularization for Sequential Confidence Calibration
Zhenghua Peng
Yuanmao Luo
Tianshui Chen
Keke Xu
Shuangping Huang
AI4TS
83
2
0
31 May 2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual
  Perception?
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?
Felix Wichmann
Robert Geirhos
61
28
0
26 May 2023
Monitoring and Adapting ML Models on Mobile Devices
Monitoring and Adapting ML Models on Mobile Devices
Wei Hao
Zixi Wang
Lauren Hong
Lingxi Li
Nader Karayanni
Chengzhi Mao
Junfeng Yang
Asaf Cidon
OffRL
70
4
0
12 May 2023
Great Models Think Alike: Improving Model Reliability via Inter-Model
  Latent Agreement
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
Ailin Deng
Miao Xiong
Bryan Hooi
205
7
0
02 May 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Agustinus Kristiadi
Alexander Immer
Runa Eschenhagen
Vincent Fortuin
BDLUQCV
80
10
0
17 Apr 2023
ASPEST: Bridging the Gap Between Active Learning and Selective
  Prediction
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction
Jiefeng Chen
Jinsung Yoon
Sayna Ebrahimi
Sercan O. Arik
S. Jha
Tomas Pfister
113
1
0
07 Apr 2023
Diffusion Denoised Smoothing for Certified and Adversarial Robust
  Out-Of-Distribution Detection
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection
Nicola Franco
Daniel Korth
J. Lorenz
Karsten Roscher
Stephan Guennemann
60
5
0
27 Mar 2023
SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution
  Detection
SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection
Jingyang Zhang
Nathan Inkawhich
Randolph Linderman
R. Luley
Yiran Chen
H. Li
OODD
71
1
0
25 Mar 2023
Bridging Precision and Confidence: A Train-Time Loss for Calibrating
  Object Detection
Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection
Muhammad Akhtar Munir
Muhammad Haris Khan
Salman Khan
Fahad Shahbaz Khan
UQCV
86
15
0
25 Mar 2023
ProtoCon: Pseudo-label Refinement via Online Clustering and Prototypical
  Consistency for Efficient Semi-supervised Learning
ProtoCon: Pseudo-label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-supervised Learning
Islam Nassar
Munawar Hayat
Ehsan Abbasnejad
Hamid Rezatofighi
Gholamreza Haffari
74
19
0
22 Mar 2023
On the Calibration and Uncertainty with Pólya-Gamma Augmentation for
  Dialog Retrieval Models
On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models
Tong Ye
Shijing Si
Jianzong Wang
Ning Cheng
Zhitao Li
Jing Xiao
116
2
0
15 Mar 2023
InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised
  Learning
InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
Zhuliang Yu
Yin Li
Yong Jae Lee
83
13
0
13 Mar 2023
Non-Parametric Outlier Synthesis
Non-Parametric Outlier Synthesis
Leitian Tao
Xuefeng Du
Xiaojin Zhu
Yixuan Li
OODD
97
108
0
06 Mar 2023
DeepLens: Interactive Out-of-distribution Data Detection in NLP Models
DeepLens: Interactive Out-of-distribution Data Detection in NLP Models
D. Song
Zhijie Wang
Yuheng Huang
Lei Ma
Tianyi Zhang
56
4
0
02 Mar 2023
Uncertainty Injection: A Deep Learning Method for Robust Optimization
Uncertainty Injection: A Deep Learning Method for Robust Optimization
W. Cui
Wei Yu
UQCVOOD
34
6
0
23 Feb 2023
VRA: Variational Rectified Activation for Out-of-distribution Detection
VRA: Variational Rectified Activation for Out-of-distribution Detection
Ming Xu
Zheng Lian
B. Liu
Jianhua Tao
OODD
43
10
0
23 Feb 2023
Fixing Overconfidence in Dynamic Neural Networks
Fixing Overconfidence in Dynamic Neural Networks
Lassi Meronen
Martin Trapp
Andrea Pilzer
Le Yang
Arno Solin
BDL
127
16
0
13 Feb 2023
Learning to Scale Temperature in Masked Self-Attention for Image
  Inpainting
Learning to Scale Temperature in Masked Self-Attention for Image Inpainting
Xiang Zhou
Yuan Zeng
Yi Gong
83
2
0
13 Feb 2023
Better Diffusion Models Further Improve Adversarial Training
Better Diffusion Models Further Improve Adversarial Training
Zekai Wang
Tianyu Pang
Chao Du
Min Lin
Weiwei Liu
Shuicheng Yan
DiffM
106
228
0
09 Feb 2023
Energy-based Out-of-Distribution Detection for Graph Neural Networks
Energy-based Out-of-Distribution Detection for Graph Neural Networks
Qitian Wu
Yiting Chen
Chenxiao Yang
Junchi Yan
OODD
129
68
0
06 Feb 2023
Trust, but Verify: Using Self-Supervised Probing to Improve
  Trustworthiness
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness
Ailin Deng
Shen Li
Miao Xiong
Zhirui Chen
Bryan Hooi
66
4
0
06 Feb 2023
Interpretable Out-Of-Distribution Detection Using Pattern Identification
Interpretable Out-Of-Distribution Detection Using Pattern Identification
Romain Xu-Darme
Julien Girard-Satabin
Darryl Hond
Gabriele Incorvaia
Zakaria Chihani
OODD
65
4
0
24 Jan 2023
Key Feature Replacement of In-Distribution Samples for
  Out-of-Distribution Detection
Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection
Jaeyoung Kim
Seo Taek Kong
Dongbin Na
Kyu-Hwan Jung
OODD
41
4
0
26 Dec 2022
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
Feng Xue
Zi He
Chuanlong Xie
Falong Tan
Zhenguo Li
OODD
123
7
0
24 Dec 2022
Rainproof: An Umbrella To Shield Text Generators From
  Out-Of-Distribution Data
Rainproof: An Umbrella To Shield Text Generators From Out-Of-Distribution Data
Maxime Darrin
Pablo Piantanida
Pierre Colombo
OODD
222
15
0
18 Dec 2022
Improving group robustness under noisy labels using predictive
  uncertainty
Improving group robustness under noisy labels using predictive uncertainty
Dongpin Oh
Dae Lee
Jeunghyun Byun
Bonggun Shin
UQCV
60
3
0
14 Dec 2022
Spurious Features Everywhere -- Large-Scale Detection of Harmful
  Spurious Features in ImageNet
Spurious Features Everywhere -- Large-Scale Detection of Harmful Spurious Features in ImageNet
Yannic Neuhaus
Maximilian Augustin
Valentyn Boreiko
Matthias Hein
AAML
134
32
0
09 Dec 2022
Self-training via Metric Learning for Source-Free Domain Adaptation of
  Semantic Segmentation
Self-training via Metric Learning for Source-Free Domain Adaptation of Semantic Segmentation
Ibrahim Batuhan Akkaya
U. Halici
TTA
94
2
0
08 Dec 2022
Block Selection Method for Using Feature Norm in Out-of-distribution
  Detection
Block Selection Method for Using Feature Norm in Out-of-distribution Detection
Yeonguk Yu
Sungho Shin
Seongju Lee
C. Jun
Kyoobin Lee
OODD
83
35
0
05 Dec 2022
Rethinking Out-of-Distribution Detection From a Human-Centric
  Perspective
Rethinking Out-of-Distribution Detection From a Human-Centric Perspective
Yao Zhu
YueFeng Chen
Xiaodan Li
Rong Zhang
Hui Xue
Xiang Tian
Rongxin Jiang
Bo Zheng
Yao-wu Chen
OODD
70
8
0
30 Nov 2022
RbA: Segmenting Unknown Regions Rejected by All
RbA: Segmenting Unknown Regions Rejected by All
Nazir Nayal
Mısra Yavuz
João F. Henriques
Fatma Guney
UQCV
99
47
0
25 Nov 2022
Delving into Out-of-Distribution Detection with Vision-Language
  Representations
Delving into Out-of-Distribution Detection with Vision-Language Representations
Yifei Ming
Ziyan Cai
Jiuxiang Gu
Yiyou Sun
W. Li
Yixuan Li
VLMOODD
130
174
0
24 Nov 2022
Promises and Pitfalls of Threshold-based Auto-labeling
Promises and Pitfalls of Threshold-based Auto-labeling
Harit Vishwakarma
Heguang Lin
Frederic Sala
Ramya Korlakai Vinayak
75
9
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
97
9
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
73
3
0
03 Nov 2022
Watermarking for Out-of-distribution Detection
Watermarking for Out-of-distribution Detection
Qizhou Wang
Feng Liu
Yonggang Zhang
Jing Zhang
Chen Gong
Tongliang Liu
Bo Han
OODD
88
32
0
27 Oct 2022
On double-descent in uncertainty quantification in overparametrized
  models
On double-descent in uncertainty quantification in overparametrized models
Lucas Clarté
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
UQCV
163
14
0
23 Oct 2022
Augmentation by Counterfactual Explanation -- Fixing an Overconfident
  Classifier
Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier
Sumedha Singla
Nihal Murali
Forough Arabshahi
Sofia Triantafyllou
Kayhan Batmanghelich
CML
122
5
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 Scarcity
Dennis Ulmer
J. Frellsen
Christian Hardmeier
267
24
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 Ensemble
Hyunsoo Cho
Choonghyun Park
Jaewoo Kang
Kang Min Yoo
Taeuk Kim
Sang-goo Lee
OODD
119
8
0
20 Oct 2022
Packed-Ensembles for Efficient Uncertainty Estimation
Packed-Ensembles for Efficient Uncertainty Estimation
Olivier Laurent
Adrien Lafage
Enzo Tartaglione
Geoffrey Daniel
Jean-Marc Martinez
Andrei Bursuc
Gianni Franchi
OODD
145
32
0
17 Oct 2022
Prediction Calibration for Generalized Few-shot Semantic Segmentation
Prediction Calibration for Generalized Few-shot Semantic Segmentation
Zhihe Lu
Sen He
Da Li
Yi-Zhe Song
Tao Xiang
ViT
71
26
0
15 Oct 2022
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
Jingkang Yang
Pengyun Wang
Dejian Zou
Zitang Zhou
Kun Ding
...
Kaiyang Zhou
Wayne Zhang
Dan Hendrycks
Yixuan Li
Ziwei Liu
OODD
93
245
0
13 Oct 2022
Robust Models are less Over-Confident
Robust Models are less Over-Confident
Julia Grabinski
Paul Gavrikov
J. Keuper
Margret Keuper
AAML
80
25
0
12 Oct 2022
Curved Representation Space of Vision Transformers
Curved Representation Space of Vision Transformers
Juyeop Kim
Junha Park
Songkuk Kim
Jongseok Lee
ViT
81
7
0
11 Oct 2022
Boosting Out-of-distribution Detection with Typical Features
Boosting Out-of-distribution Detection with Typical Features
Yao Zhu
YueFeng Chen
Chuanlong Xie
Xiaodan Li
Rong Zhang
Hui Xue
Xiang Tian
Bolun Zheng
Yao-wu Chen
OODD
160
53
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 Models
Julius Gonsior
C. Falkenberg
Silvio Magino
Anja Reusch
Maik Thiele
Wolfgang Lehner
UQCV
81
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 Objects
Kira Maag
Robin Shing Moon Chan
Svenja Uhlemeyer
K. Kowol
Hanno Gottschalk
104
19
0
05 Oct 2022
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