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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
Out-Of-Distribution Detection In Unsupervised Continual Learning
Out-Of-Distribution Detection In Unsupervised Continual Learning
Jiangpeng He
Fengqing Zhu
OODD
115
14
0
12 Apr 2022
Full-Spectrum Out-of-Distribution Detection
Full-Spectrum Out-of-Distribution DetectionInternational Journal of Computer Vision (IJCV), 2022
Jingkang Yang
Kaiyang Zhou
Ziwei Liu
OODD
201
75
0
11 Apr 2022
Efficient Test-Time Model Adaptation without Forgetting
Efficient Test-Time Model Adaptation without ForgettingInternational Conference on Machine Learning (ICML), 2022
Shuaicheng Niu
Jiaxiang Wu
Yifan Zhang
Yaofo Chen
S. Zheng
P. Zhao
Zhuliang Yu
OODVLMTTA
337
482
0
06 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
240
21
0
06 Apr 2022
Energy-based Latent Aligner for Incremental Learning
Energy-based Latent Aligner for Incremental LearningComputer Vision and Pattern Recognition (CVPR), 2022
K. J. Joseph
Salman Khan
Fahad Shahbaz Khan
Rao Muhammad Anwer
V. Balasubramanian
CLL
283
55
0
28 Mar 2022
Bi-level Doubly Variational Learning for Energy-based Latent Variable
  Models
Bi-level Doubly Variational Learning for Energy-based Latent Variable ModelsComputer Vision and Pattern Recognition (CVPR), 2022
Ge Kan
Jinhu Lu
Tian Wang
Baochang Zhang
Aichun Zhu
Lei Huang
Guodong Guo
H. Snoussi
222
8
0
24 Mar 2022
Out of Distribution Detection, Generalization, and Robustness Triangle
  with Maximum Probability Theorem
Out of Distribution Detection, Generalization, and Robustness Triangle with Maximum Probability Theorem
Amir Emad Marvasti
Ehsan Emad Marvasti
Ulas Bagci
OOD
172
0
0
23 Mar 2022
Boost Test-Time Performance with Closed-Loop Inference
Boost Test-Time Performance with Closed-Loop Inference
Shuaicheng Niu
Jiaxiang Wu
Yifan Zhang
Guanghui Xu
Haokun Li
Peilin Zhao
Junzhou Huang
Yaowei Wang
Zhuliang Yu
289
7
0
21 Mar 2022
ViM: Out-Of-Distribution with Virtual-logit Matching
ViM: Out-Of-Distribution with Virtual-logit MatchingComputer Vision and Pattern Recognition (CVPR), 2022
Haoqi Wang
Zhizhong Li
Xue Jiang
Wayne Zhang
OODD
313
429
0
21 Mar 2022
Emulating Quantum Dynamics with Neural Networks via Knowledge
  Distillation
Emulating Quantum Dynamics with Neural Networks via Knowledge DistillationFrontiers in Materials (Front. Mater.), 2022
Yu Yao
C. Cao
S. Haas
Mahak Agarwal
Divya Khanna
M. Abram
231
4
0
19 Mar 2022
Are Vision Transformers Robust to Spurious Correlations?
Are Vision Transformers Robust to Spurious Correlations?International Journal of Computer Vision (IJCV), 2022
Soumya Suvra Ghosal
Yifei Ming
Shouqing Yang
ViT
236
42
0
17 Mar 2022
A Continual Learning Framework for Adaptive Defect Classification and
  Inspection
A Continual Learning Framework for Adaptive Defect Classification and InspectionJournal of QualityTechnology (JQT), 2022
Wenbo Sun
Raed Al Kontar
Judy Jin
Tzyy-Shuh Chang
119
11
0
16 Mar 2022
Igeood: An Information Geometry Approach to Out-of-Distribution
  Detection
Igeood: An Information Geometry Approach to Out-of-Distribution DetectionInternational Conference on Learning Representations (ICLR), 2022
Eduardo Dadalto Camara Gomes
F. Alberge
Pierre Duhamel
Pablo Piantanida
OODD
271
30
0
15 Mar 2022
Learning Discriminative Representations and Decision Boundaries for Open
  Intent Detection
Learning Discriminative Representations and Decision Boundaries for Open Intent DetectionIEEE/ACM Transactions on Audio Speech and Language Processing (TASLP), 2022
Hanlei Zhang
Huan Xu
Shaojie Zhao
Qianrui Zhou
216
28
0
11 Mar 2022
How to Exploit Hyperspherical Embeddings for Out-of-Distribution
  Detection?
How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?International Conference on Learning Representations (ICLR), 2022
Yifei Ming
Yiyou Sun
Ousmane Amadou Dia
Shouqing Yang
OODD
416
128
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 WildComputer Vision and Pattern Recognition (CVPR), 2022
Xuefeng Du
Xin Eric Wang
Gabriel Gozum
Shouqing Yang
OODD
255
107
0
08 Mar 2022
Concept-based Explanations for Out-Of-Distribution Detectors
Concept-based Explanations for Out-Of-Distribution DetectorsInternational Conference on Machine Learning (ICML), 2022
Jihye Choi
Jayaram Raghuram
Ryan Feng
Jiefeng Chen
S. Jha
Atul Prakash
OODD
201
17
0
04 Mar 2022
Learning Neural Set Functions Under the Optimal Subset Oracle
Learning Neural Set Functions Under the Optimal Subset OracleNeural Information Processing Systems (NeurIPS), 2022
Chinmay Pani
Qifeng Bai
Qinliang Su
Yingzhen Li
P. Zhao
Yatao Bian
BDL
357
10
0
03 Mar 2022
Fine-grained TLS services classification with reject option
Fine-grained TLS services classification with reject option
Jan Luxemburk
T. Čejka
121
40
0
24 Feb 2022
Computer Aided Diagnosis and Out-of-Distribution Detection in Glaucoma
  Screening Using Color Fundus Photography
Computer Aided Diagnosis and Out-of-Distribution Detection in Glaucoma Screening Using Color Fundus Photography
Satoshi Kondo
Satoshi Kasai
Kosuke Hirasawa
61
2
0
24 Feb 2022
Training OOD Detectors in their Natural Habitats
Training OOD Detectors in their Natural HabitatsInternational Conference on Machine Learning (ICML), 2022
Julian Katz-Samuels
Julia B. Nakhleh
Robert D. Nowak
Shouqing Yang
OODD
231
104
0
07 Feb 2022
Nonparametric Uncertainty Quantification for Single Deterministic Neural
  Network
Nonparametric Uncertainty Quantification for Single Deterministic Neural NetworkNeural Information Processing Systems (NeurIPS), 2022
Nikita Kotelevskii
A. Artemenkov
Kirill Fedyanin
Fedor Noskov
Alexander Fishkov
Artem Shelmanov
Artem Vazhentsev
Aleksandr Petiushko
Maxim Panov
UQCVBDL
179
42
0
07 Feb 2022
Mapping DNN Embedding Manifolds for Network Generalization Prediction
Mapping DNN Embedding Manifolds for Network Generalization Prediction
Molly O'Brien
Julia V. Bukowski
Mathias Unberath
Aria Pezeshk
Gregory Hager
AI4CE
107
0
0
03 Feb 2022
Active Learning Over Multiple Domains in Natural Language Tasks
Active Learning Over Multiple Domains in Natural Language Tasks
Shayne Longpre
Julia Reisler
E. G. Huang
Yi Lu
Andrew J. Frank
Nikhil Ramesh
Chris DuBois
OOD
228
16
0
01 Feb 2022
Out of Distribution Detection on ImageNet-O
Out of Distribution Detection on ImageNet-O
Anugya Srivastava
S. Jain
Mugdha Thigle
OOD
206
6
0
23 Jan 2022
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution
  Detection
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution DetectionAAAI Conference on Artificial Intelligence (AAAI), 2022
R. Kaur
Susmit Jha
Anirban Roy
Sangdon Park
Guang Cheng
O. Sokolsky
Insup Lee
OODD
193
52
0
07 Jan 2022
Dense Out-of-Distribution Detection by Robust Learning on Synthetic
  Negative Data
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative DataItalian National Conference on Sensors (INS), 2021
Matej Grcić
Petra Bevandić
Zoran Kalafatić
Sinivsa vSegvić
355
15
0
23 Dec 2021
Out-of-distribution Detection with Boundary Aware Learning
Out-of-distribution Detection with Boundary Aware LearningEuropean Conference on Computer Vision (ECCV), 2021
Sen Pei
Xin Zhang
Bin Fan
Gaofeng Meng
OODD
152
12
0
22 Dec 2021
Energy-bounded Learning for Robust Models of Code
Nghi D. Q. Bui
Yijun Yu
OODD
214
2
0
20 Dec 2021
WOOD: Wasserstein-based Out-of-Distribution Detection
WOOD: Wasserstein-based Out-of-Distribution Detection
Yinan Wang
Wenbo Sun
Jionghua Jin
Zhen Kong
Xiaowei Yue
OODD
114
13
0
13 Dec 2021
Hyperdimensional Feature Fusion for Out-Of-Distribution Detection
Hyperdimensional Feature Fusion for Out-Of-Distribution Detection
Samuel Wilson
Tobias Fischer
Niko Sünderhauf
Feras Dayoub
OODD
257
21
0
10 Dec 2021
Active Learning for Domain Adaptation: An Energy-Based Approach
Active Learning for Domain Adaptation: An Energy-Based Approach
Binhui Xie
Longhui Yuan
Shuang Li
Chi Harold Liu
Xinjing Cheng
Guoren Wang
237
140
0
02 Dec 2021
Provable Guarantees for Understanding Out-of-distribution Detection
Provable Guarantees for Understanding Out-of-distribution Detection
Peyman Morteza
Shouqing Yang
OODD
199
102
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
191
12
0
01 Dec 2021
A Unified Benchmark for the Unknown Detection Capability of Deep Neural
  Networks
A Unified Benchmark for the Unknown Detection Capability of Deep Neural Networks
Jihyo Kim
Jiin Koo
Sangheum Hwang
UQCV
311
23
0
01 Dec 2021
Understanding Out-of-distribution: A Perspective of Data Dynamics
Understanding Out-of-distribution: A Perspective of Data Dynamics
Dyah Adila
Luan Tuyen Chau
178
13
0
29 Nov 2021
SLA$^2$P: Self-supervised Anomaly Detection with Adversarial
  Perturbation
SLA2^22P: Self-supervised Anomaly Detection with Adversarial Perturbation
Yizhou Wang
Can Qin
Rongzhe Wei
Yi Tian Xu
Yue Bai
Y. Fu
AAML
203
7
0
25 Nov 2021
ReAct: Out-of-distribution Detection With Rectified Activations
ReAct: Out-of-distribution Detection With Rectified Activations
Yiyou Sun
Chuan Guo
Shouqing Yang
OODD
455
575
0
24 Nov 2021
Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on
  Complex Urban Driving Scenes
Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
Yu Tian
Yuyuan Liu
Guansong Pang
Fengbei Liu
Yuanhong Chen
G. Carneiro
465
110
0
24 Nov 2021
DICE: Leveraging Sparsification for Out-of-Distribution Detection
DICE: Leveraging Sparsification for Out-of-Distribution Detection
Yiyou Sun
Shouqing Yang
OODD
358
198
0
18 Nov 2021
Class-wise Thresholding for Robust Out-of-Distribution Detection
Class-wise Thresholding for Robust Out-of-Distribution Detection
Matteo Guarrera
Baihong Jin
Tung-Wei Lin
Maria A. Zuluaga
Yuxin Chen
Alberto L. Sangiovanni-Vincentelli
OODDOOD
270
4
0
28 Oct 2021
Exploring Covariate and Concept Shift for Detection and Calibration of
  Out-of-Distribution Data
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data
Junjiao Tian
Yen-Change Hsu
Yilin Shen
Hongxia Jin
Z. Kira
OODD
290
8
0
28 Oct 2021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution
  Detection: Solutions and Future Challenges
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
Mohammadreza Salehi
Hossein Mirzaei
Dan Hendrycks
Shouqing Yang
M. Rohban
Mohammad Sabokrou
OOD
672
223
0
26 Oct 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
171
40
0
26 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node
  Classification
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
UQCVBDL
316
104
0
26 Oct 2021
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A SurveyInternational Journal of Computer Vision (IJCV), 2021
Jingkang Yang
Kaiyang Zhou
Shouqing Yang
Ziwei Liu
768
1,207
0
21 Oct 2021
EBJR: Energy-Based Joint Reasoning for Adaptive Inference
EBJR: Energy-Based Joint Reasoning for Adaptive InferenceBritish Machine Vision Conference (BMVC), 2021
Mohammad Akbari
Amin Banitalebi-Dehkordi
Yong Zhang
BDLMQ
147
7
0
20 Oct 2021
Natural Attribute-based Shift Detection
Natural Attribute-based Shift Detection
Jeonghoon Park
Jimin Hong
Radhika Dua
Daehoon Gwak
Shouqing Yang
Jaegul Choo
Edward Choi
OOD
147
3
0
18 Oct 2021
Single Layer Predictive Normalized Maximum Likelihood for
  Out-of-Distribution Detection
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
Koby Bibas
M. Feder
Tal Hassner
OODD
147
27
0
18 Oct 2021
Well-classified Examples are Underestimated in Classification with Deep
  Neural Networks
Well-classified Examples are Underestimated in Classification with Deep Neural Networks
Guangxiang Zhao
Wenkai Yang
Xuancheng Ren
Lei Li
Hao Sun
Xu Sun
248
15
0
13 Oct 2021
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