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Training Confidence-calibrated Classifiers for Detecting
  Out-of-Distribution Samples

Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples

26 November 2017
Kimin Lee
Honglak Lee
Kibok Lee
Jinwoo Shin
    OODD
ArXivPDFHTML

Papers citing "Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples"

50 / 174 papers shown
Title
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
Chen Liang
Wenguan Wang
Jiaxu Miao
Yi Yang
VLM
36
117
0
05 Oct 2022
Feature Decoupling in Self-supervised Representation Learning for Open
  Set Recognition
Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition
Jingyun Jia
P. Chan
BDL
19
2
0
28 Sep 2022
Saliency Guided Adversarial Training for Learning Generalizable Features
  with Applications to Medical Imaging Classification System
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System
Xin Li
Yao Qiang
Chengyin Li
Sijia Liu
D. Zhu
OOD
MedIm
29
4
0
09 Sep 2022
SAFE: Sensitivity-Aware Features for Out-of-Distribution Object
  Detection
SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection
Samuel Wilson
Tobias Fischer
Feras Dayoub
Dimity Miller
Niko Sünderhauf
OODD
31
29
0
29 Aug 2022
Semantic Driven Energy based Out-of-Distribution Detection
Semantic Driven Energy based Out-of-Distribution Detection
Abhishek Joshi
Sathish Chalasani
K. N. Iyer
OODD
29
4
0
23 Aug 2022
ShortcutLens: A Visual Analytics Approach for Exploring Shortcuts in
  Natural Language Understanding Dataset
ShortcutLens: A Visual Analytics Approach for Exploring Shortcuts in Natural Language Understanding Dataset
Zhihua Jin
Xingbo Wang
Furui Cheng
Chunhui Sun
Qun Liu
Huamin Qu
32
9
0
17 Aug 2022
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data
R. Kaur
Kaustubh Sridhar
Sangdon Park
Susmit Jha
Anirban Roy
O. Sokolsky
Insup Lee
OODD
AI4TS
144
0
0
24 Jul 2022
Time Is MattEr: Temporal Self-supervision for Video Transformers
Time Is MattEr: Temporal Self-supervision for Video Transformers
Sukmin Yun
Jaehyung Kim
Dongyoon Han
Hwanjun Song
Jung-Woo Ha
Jinwoo Shin
ViT
15
12
0
19 Jul 2022
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier
Bartosz Wójcik
J. Grela
Marek Śmieja
Krzysztof Misztal
Jacek Tabor
UQCV
33
4
0
28 Jun 2022
POEM: Out-of-Distribution Detection with Posterior Sampling
POEM: Out-of-Distribution Detection with Posterior Sampling
Yifei Ming
Ying Fan
Yixuan Li
OODD
29
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
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
15
25
0
20 Jun 2022
Gray Learning from Non-IID Data with Out-of-distribution Samples
Gray Learning from Non-IID Data with Out-of-distribution Samples
Zhilin Zhao
LongBing Cao
Changbao Wang
OOD
OODD
29
1
0
19 Jun 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
45
23
0
20 May 2022
Self-Supervised Masking for Unsupervised Anomaly Detection and
  Localization
Self-Supervised Masking for Unsupervised Anomaly Detection and Localization
Chaoqin Huang
Qinwei Xu
Yanfeng Wang
Yu Wang
Ya-Qin Zhang
37
66
0
13 May 2022
Norm-Scaling for Out-of-Distribution Detection
Norm-Scaling for Out-of-Distribution Detection
Deepak Ravikumar
Kaushik Roy
OODD
UQCV
19
2
0
06 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via
  Distance-Awareness
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
18
48
0
01 May 2022
Out-of-Distribution Detection with Deep Nearest Neighbors
Out-of-Distribution Detection with Deep Nearest Neighbors
Yiyou Sun
Yifei Ming
Xiaojin Zhu
Yixuan Li
OODD
19
488
0
13 Apr 2022
Effective Out-of-Distribution Detection in Classifier Based on
  PEDCC-Loss
Effective Out-of-Distribution Detection in Classifier Based on PEDCC-Loss
Qiuyu Zhu
Guohui Zheng
Yingying Yan
OODD
14
8
0
10 Apr 2022
RODD: A Self-Supervised Approach for Robust Out-of-Distribution
  Detection
RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection
Umar Khalid
Ashkan Esmaeili
Nazmul Karim
Nazanin Rahnavard
OODD
39
12
0
06 Apr 2022
Efficient, Uncertainty-based Moderation of Neural Networks Text
  Classifiers
Efficient, Uncertainty-based Moderation of Neural Networks Text Classifiers
J. S. Andersen
W. Maalej
14
9
0
04 Apr 2022
Estimating the Uncertainty in Emotion Class Labels with
  Utterance-Specific Dirichlet Priors
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors
Wen Wu
C. Zhang
Xixin Wu
P. Woodland
48
14
0
08 Mar 2022
Unknown-Aware Object Detection: Learning What You Don't Know from Videos
  in the Wild
Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild
Xuefeng Du
Xin Wang
Gabriel Gozum
Yixuan Li
OODD
43
91
0
08 Mar 2022
Training OOD Detectors in their Natural Habitats
Training OOD Detectors in their Natural Habitats
Julian Katz-Samuels
Julia B. Nakhleh
Robert D. Nowak
Yixuan Li
OODD
24
90
0
07 Feb 2022
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network
  Sensors and its Application in Process Control
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network Sensors and its Application in Process Control
J. Pulsipher
Luke D. J. Coutinho
Tyler A. Soderstrom
Victor M. Zavala
HAI
12
7
0
03 Feb 2022
Out-of-distribution Detection with Boundary Aware Learning
Out-of-distribution Detection with Boundary Aware Learning
Sen Pei
Xin Zhang
Bin Fan
Gaofeng Meng
OODD
21
8
0
22 Dec 2021
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures
Dan Hendrycks
Andy Zou
Mantas Mazeika
Leonard Tang
Bo-wen Li
D. Song
Jacob Steinhardt
UQCV
23
136
0
09 Dec 2021
Benchmark for Out-of-Distribution Detection in Deep Reinforcement
  Learning
Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning
Aaqib Parvez Mohammed
Matias Valdenegro-Toro
OOD
OffRL
16
10
0
05 Dec 2021
Provable Guarantees for Understanding Out-of-distribution Detection
Provable Guarantees for Understanding Out-of-distribution Detection
Peyman Morteza
Yixuan Li
OODD
30
86
0
01 Dec 2021
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Xiaoxiao Sun
Yunzhong Hou
Hongdong Li
Liang Zheng
13
11
0
01 Dec 2021
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution
  Detection
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution Detection
Nikolaos Dionelis
Mehrdad Yaghoobi
Sotirios A. Tsaftaris
OODD
16
4
0
30 Nov 2021
Statistical Perspectives on Reliability of Artificial Intelligence
  Systems
Statistical Perspectives on Reliability of Artificial Intelligence Systems
Yili Hong
J. Lian
Li Xu
Jie Min
Yueyao Wang
Laura J. Freeman
Xinwei Deng
25
30
0
09 Nov 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift
  Detection
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park
Anas Awadalla
Tadayoshi Kohno
Shwetak N. Patel
OOD
30
29
0
26 Oct 2021
Addressing out-of-distribution label noise in webly-labelled data
Addressing out-of-distribution label noise in webly-labelled data
Paul Albert
Diego Ortego
Eric Arazo
Noel E. O'Connor
Kevin McGuinness
NoLa
16
16
0
26 Oct 2021
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
185
877
0
21 Oct 2021
A novel network training approach for open set image recognition
A novel network training approach for open set image recognition
Md Tahmid Hossaina
S. Teng
Guojun Lu
Ferdous Sohel
21
0
0
27 Sep 2021
SoK: Machine Learning Governance
SoK: Machine Learning Governance
Varun Chandrasekaran
Hengrui Jia
Anvith Thudi
Adelin Travers
Mohammad Yaghini
Nicolas Papernot
38
16
0
20 Sep 2021
GOLD: Improving Out-of-Scope Detection in Dialogues using Data
  Augmentation
GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation
Derek Chen
Zhou Yu
24
31
0
07 Sep 2021
NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task
  Models
NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task Models
Myeongjun Jang
Thomas Lukasiewicz
24
4
0
29 Aug 2021
NGC: A Unified Framework for Learning with Open-World Noisy Data
NGC: A Unified Framework for Learning with Open-World Noisy Data
Zhi-Fan Wu
Tong Wei
Jianwen Jiang
Chaojie Mao
Mingqian Tang
Yu-Feng Li
11
80
0
25 Aug 2021
Revealing the Distributional Vulnerability of Discriminators by Implicit
  Generators
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators
Zhilin Zhao
LongBing Cao
Kun-Yu Lin
29
11
0
23 Aug 2021
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue
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
143
30
0
13 Aug 2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Yezhen Wang
Bo-wen Li
Tong Che
Kaiyang Zhou
Ziwei Liu
Dongsheng Li
UQCV
22
47
0
27 Jul 2021
On the Importance of Regularisation & Auxiliary Information in OOD
  Detection
On the Importance of Regularisation & Auxiliary Information in OOD Detection
John Mitros
Brian Mac Namee
21
2
0
15 Jul 2021
Detecting when pre-trained nnU-Net models fail silently for Covid-19
  lung lesion segmentation
Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
Camila González
Karol Gotkowski
A. Bucher
Ricarda Fischbach
Isabel Kaltenborn
Anirban Mukhopadhyay
21
31
0
13 Jul 2021
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDL
UQCV
OOD
35
1,109
0
07 Jul 2021
Graceful Degradation and Related Fields
Graceful Degradation and Related Fields
J. Dymond
31
4
0
21 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks
Being a Bit Frequentist Improves Bayesian Neural Networks
Agustinus Kristiadi
Matthias Hein
Philipp Hennig
BDL
UQCV
20
15
0
18 Jun 2021
Meta-Calibration: Learning of Model Calibration Using Differentiable
  Expected Calibration Error
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error
Ondrej Bohdal
Yongxin Yang
Timothy M. Hospedales
UQCV
OOD
43
21
0
17 Jun 2021
Out-of-Scope Intent Detection with Self-Supervision and Discriminative
  Training
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training
Li-Ming Zhan
Haowen Liang
Bo Liu
Lu Fan
Xiao-Ming Wu
Albert Y. S. Lam
OODD
13
75
0
16 Jun 2021
Robust Out-of-Distribution Detection on Deep Probabilistic Generative
  Models
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
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