ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.03759
  4. Cited By
Energy-based Out-of-distribution Detection
v1v2v3v4 (latest)

Energy-based Out-of-distribution Detection

8 October 2020
Weitang Liu
Xiaoyun Wang
John Douglas Owens
Shouqing Yang
    OODD
ArXiv (abs)PDFHTML

Papers citing "Energy-based Out-of-distribution Detection"

50 / 958 papers shown
Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic
  Uncertainty
Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic UncertaintyInternational Conference on Learning Representations (ICLR), 2021
Jeffrey Willette
Haebeom Lee
Juho Lee
Sung Ju Hwang
OODDOOD
219
2
0
12 Oct 2021
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?International Conference on Learning Representations (ICLR), 2021
S. Vaze
Kai Han
Andrea Vedaldi
Andrew Zisserman
BDL
543
541
0
12 Oct 2021
Estimating the confidence of speech spoofing countermeasure
Estimating the confidence of speech spoofing countermeasureIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
Xin Wang
Junichi Yamagishi
77
9
0
10 Oct 2021
An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in
  Safety-Critical Applications
An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in Safety-Critical ApplicationsReliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2021
Taotao Zhou
E. Droguett
A. Mosleh
F. Chan
EDL
123
61
0
08 Oct 2021
Objects in Semantic Topology
Objects in Semantic Topology
Shuo Yang
Pei Sun
Yi Jiang
Xiaobo Xia
Ruiheng Zhang
Zehuan Yuan
Changhu Wang
Ping Luo
Min Xu
ObjD
254
36
0
06 Oct 2021
On the Importance of Gradients for Detecting Distributional Shifts in
  the Wild
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Rui Huang
Andrew Geng
Shouqing Yang
654
414
0
01 Oct 2021
Can multi-label classification networks know what they don't know?
Can multi-label classification networks know what they don't know?
Haoran Wang
Weitang Liu
Alex E. Bocchieri
Shouqing Yang
OODD
343
127
0
29 Sep 2021
One-Class Meta-Learning: Towards Generalizable Few-Shot Open-Set
  Classification
One-Class Meta-Learning: Towards Generalizable Few-Shot Open-Set Classification
Jedrzej Kozerawski
M. Turk
VLMMQ
130
5
0
14 Sep 2021
On the Impact of Spurious Correlation for Out-of-distribution Detection
On the Impact of Spurious Correlation for Out-of-distribution Detection
Yifei Ming
Hang Yin
Shouqing Yang
OODD
366
75
0
12 Sep 2021
No True State-of-the-Art? OOD Detection Methods are Inconsistent across
  Datasets
No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets
Fahim Tajwar
Ananya Kumar
Sang Michael Xie
Abigail Z. Jacobs
OODD
217
32
0
12 Sep 2021
Anomaly Detection of Defect using Energy of Point Pattern Features
  within Random Finite Set Framework
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set FrameworkEngineering applications of artificial intelligence (EAAI), 2021
Ammar Mansoor Kamoona
A. Gostar
A. Bab-Hadiashar
R. Hoseinnezhad
124
19
0
27 Aug 2021
Semantically Coherent Out-of-Distribution Detection
Semantically Coherent Out-of-Distribution DetectionIEEE International Conference on Computer Vision (ICCV), 2021
Jingkang Yang
Haoqi Wang
Xue Jiang
Xiaopeng Yan
Huabin Zheng
Wayne Zhang
Ziwei Liu
OODD
244
148
0
26 Aug 2021
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence IssueIEEE International Conference on Computer Vision (ICCV), 2021
Keke Tang
Dingruibo Miao
Weilong Peng
Jianpeng Wu
Yawen Shi
Zhaoquan Gu
Zhihong Tian
Wenping Wang
OODD
331
34
0
13 Aug 2021
Pixyz: a Python library for developing deep generative models
Pixyz: a Python library for developing deep generative models
Masahiro Suzuki
T. Kaneko
Y. Matsuo
AI4CE
187
3
0
28 Jul 2021
Energy-based Unknown Intent Detection with Data Manipulation
Energy-based Unknown Intent Detection with Data ManipulationFindings (Findings), 2021
Yawen Ouyang
Jiasheng Ye
Yu Chen
Xinyu Dai
Shujian Huang
Jiajun Chen
111
24
0
27 Jul 2021
Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers
Clipped Hyperbolic Classifiers Are Super-Hyperbolic ClassifiersComputer Vision and Pattern Recognition (CVPR), 2021
Yunhui Guo
Xudong Wang
Yubei Chen
Stella X. Yu
191
65
0
23 Jul 2021
Constraints Penalized Q-learning for Safe Offline Reinforcement Learning
Constraints Penalized Q-learning for Safe Offline Reinforcement LearningAAAI Conference on Artificial Intelligence (AAAI), 2021
Haoran Xu
Xianyuan Zhan
Xiangyu Zhu
OffRL
378
106
0
19 Jul 2021
On the Importance of Regularisation & Auxiliary Information in OOD
  Detection
On the Importance of Regularisation & Auxiliary Information in OOD DetectionInternational Conference on Neural Information Processing (ICONIP), 2021
John Mitros
Brian Mac Namee
248
2
0
15 Jul 2021
A modular U-Net for automated segmentation of X-ray tomography images in
  composite materials
A modular U-Net for automated segmentation of X-ray tomography images in composite materialsFrontiers in Materials (Front. Mater.), 2021
João P C Bertoldo
Etienne Decencière
David Ryckelynck
H. Proudhon
137
16
0
15 Jul 2021
Thinkback: Task-SpecificOut-of-Distribution Detection
Thinkback: Task-SpecificOut-of-Distribution Detection
Lixuan Yang
Dario Rossi
OODD
82
1
0
13 Jul 2021
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object
  Detectors
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object DetectorsIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Tobias Riedlinger
Matthias Rottmann
Marius Schubert
Hanno Gottschalk
BDLUQCV
284
15
0
09 Jul 2021
On Out-of-distribution Detection with Energy-based Models
On Out-of-distribution Detection with Energy-based Models
Sven Elflein
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
OODD
161
22
0
03 Jul 2021
Scene Uncertainty and the Wellington Posterior of Deterministic Image
  Classifiers
Scene Uncertainty and the Wellington Posterior of Deterministic Image Classifiers
Stephanie Tsuei
Aditya Golatkar
Stefano Soatto
UQCV
173
0
0
25 Jun 2021
Towards Consistent Predictive Confidence through Fitted Ensembles
Towards Consistent Predictive Confidence through Fitted EnsemblesIEEE International Joint Conference on Neural Network (IJCNN), 2021
Navid Kardan
Ankit Sharma
Kenneth O. Stanley
FedMLOODD
147
8
0
22 Jun 2021
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
Open-set Label Noise Can Improve Robustness Against Inherent Label NoiseNeural Information Processing Systems (NeurIPS), 2021
Jianguo Huang
Lue Tao
Renchunzi Xie
Bo An
NoLa
285
101
0
21 Jun 2021
Noise-robust Graph Learning by Estimating and Leveraging Pairwise
  Interactions
Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions
Xuefeng Du
Tian Bian
Yu Rong
Bo Han
Tongliang Liu
Qifeng Bai
Wenbing Huang
Shouqing Yang
Junzhou Huang
NoLa
229
20
0
14 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and PrimerACM Computing Surveys (CSUR), 2021
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zinan Lin
J. Yadawa
303
44
0
09 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free
Provably Robust Detection of Out-of-distribution Data (almost) for freeNeural Information Processing Systems (NeurIPS), 2021
Alexander Meinke
Julian Bitterwolf
Matthias Hein
OODD
215
21
0
08 Jun 2021
Mixture Outlier Exposure: Towards Out-of-Distribution Detection in
  Fine-grained Environments
Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained EnvironmentsIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Jingyang Zhang
Nathan Inkawhich
Randolph Linderman
Yiran Chen
Xue Yang
OODD
297
72
0
07 Jun 2021
Energy Aligning for Biased Models
Energy Aligning for Biased Models
Bowen Zhao
Chen Chen
Qi Ju
Shutao Xia
101
1
0
07 Jun 2021
Energy-Based Learning for Cooperative Games, with Applications to
  Valuation Problems in Machine Learning
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine LearningInternational Conference on Learning Representations (ICLR), 2021
Yatao Bian
Yu Rong
Qifeng Bai
Jiaxiang Wu
Andreas Krause
Junzhou Huang
436
17
0
05 Jun 2021
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
Two Coupled Rejection Metrics Can Tell Adversarial Examples ApartComputer Vision and Pattern Recognition (CVPR), 2021
Tianyu Pang
Huishuai Zhang
Di He
Yinpeng Dong
Hang Su
Wei Chen
Jun Zhu
Tie-Yan Liu
AAML
217
23
0
31 May 2021
Enhanced Isotropy Maximization Loss: Seamless and High-Performance
  Out-of-Distribution Detection Simply Replacing the SoftMax Loss
Enhanced Isotropy Maximization Loss: Seamless and High-Performance Out-of-Distribution Detection Simply Replacing the SoftMax Loss
David Macêdo
Teresa B Ludermir
OODD
446
15
0
30 May 2021
Energy-Based Anomaly Detection and Localization
Energy-Based Anomaly Detection and Localization
Ergin Utku Genc
Nilesh A. Ahuja
I. Ndiour
Omesh Tickoo
112
6
0
07 May 2021
Iterative Human and Automated Identification of Wildlife Images
Iterative Human and Automated Identification of Wildlife ImagesNature Machine Intelligence (Nat. Mach. Intell.), 2021
Zhongqi Miao
Ziwei Liu
Kaitlyn M. Gaynor
M. Palmer
Stella X. Yu
W. Getz
283
55
0
05 May 2021
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic
  Space
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic SpaceComputer Vision and Pattern Recognition (CVPR), 2021
Rui Huang
Shouqing Yang
OODD
363
294
0
05 May 2021
MOOD: Multi-level Out-of-distribution Detection
MOOD: Multi-level Out-of-distribution DetectionComputer Vision and Pattern Recognition (CVPR), 2021
Ziqian Lin
Sreya . Dutta Roy
Shouqing Yang
OODD
185
125
0
30 Apr 2021
Neural Mean Discrepancy for Efficient Out-of-Distribution Detection
Neural Mean Discrepancy for Efficient Out-of-Distribution DetectionComputer Vision and Pattern Recognition (CVPR), 2021
Xin Dong
Junfeng Guo
Ang Li
W. Ting
Cong Liu
H. T. Kung
OODD
337
67
0
23 Apr 2021
Contrastive Out-of-Distribution Detection for Pretrained Transformers
Contrastive Out-of-Distribution Detection for Pretrained TransformersConference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Wenxuan Zhou
Fangyu Liu
Muhao Chen
228
111
0
18 Apr 2021
Out-of-Distribution Detection for Dermoscopic Image Classification
Out-of-Distribution Detection for Dermoscopic Image Classification
Mohammadreza Mohseni
J. Yap
William Yolland
M. Razmara
S. Atkins
100
1
0
15 Apr 2021
Elsa: Energy-based learning for semi-supervised anomaly detection
Elsa: Energy-based learning for semi-supervised anomaly detectionBritish Machine Vision Conference (BMVC), 2021
Sungwon Han
Hyeonho Song
Seungeon Lee
Sungwon Park
M. Cha
205
14
0
29 Mar 2021
Are all outliers alike? On Understanding the Diversity of Outliers for
  Detecting OODs
Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs
R. Kaur
Susmit Jha
Anirban Roy
O. Sokolsky
Insup Lee
148
14
0
23 Mar 2021
Towards Open World Object Detection
Towards Open World Object DetectionComputer Vision and Pattern Recognition (CVPR), 2021
K. J. Joseph
Salman Khan
Fahad Shahbaz Khan
V. Balasubramanian
ObjD
250
541
0
03 Mar 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition
Counterfactual Zero-Shot and Open-Set Visual RecognitionComputer Vision and Pattern Recognition (CVPR), 2021
Zhongqi Yue
Tan Wang
Hanwang Zhang
Qianru Sun
Xiansheng Hua
BDL
426
224
0
01 Mar 2021
A statistical framework for efficient out of distribution detection in
  deep neural networks
A statistical framework for efficient out of distribution detection in deep neural networksInternational Conference on Learning Representations (ICLR), 2021
Matan Haroush
Tzviel Frostig
R. Heller
Daniel Soudry
OODD
252
39
0
25 Feb 2021
Deep Deterministic Uncertainty: A Simple Baseline
Deep Deterministic Uncertainty: A Simple BaselineComputer Vision and Pattern Recognition (CVPR), 2021
Jishnu Mukhoti
Andreas Kirsch
Joost R. van Amersfoort
Juil Sock
Y. Gal
UDUQCVPERBDL
444
215
0
23 Feb 2021
Unsupervised Energy-based Out-of-distribution Detection using
  Stiefel-Restricted Kernel Machine
Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel MachineIEEE International Joint Conference on Neural Network (IJCNN), 2021
F. Tonin
Arun Pandey
Panagiotis Patrinos
Johan A. K. Suykens
OODD
191
14
0
16 Feb 2021
Model Rectification via Unknown Unknowns Extraction from Deployment
  Samples
Model Rectification via Unknown Unknowns Extraction from Deployment Samples
B. Abrahao
Zechuan Wang
Haider Ahmed
Yuchen Zhu
114
0
0
08 Feb 2021
Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution
  Detection
Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection
Deepak Ravikumar
Sangamesh Kodge
Isha Garg
Kaushik Roy
OODD
163
5
0
15 Dec 2020
Perfect density models cannot guarantee anomaly detection
Perfect density models cannot guarantee anomaly detection
Charline Le Lan
Laurent Dinh
404
54
0
07 Dec 2020
Previous
123...181920
Next