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Predictive Uncertainty Estimation via Prior Networks
v1v2v3v4 (latest)

Predictive Uncertainty Estimation via Prior Networks

Neural Information Processing Systems (NeurIPS), 2018
28 February 2018
A. Malinin
Mark Gales
    UDBDLEDLUQCVPER
ArXiv (abs)PDFHTML

Papers citing "Predictive Uncertainty Estimation via Prior Networks"

50 / 576 papers shown
Simple Regularisation for Uncertainty-Aware Knowledge Distillation
Simple Regularisation for Uncertainty-Aware Knowledge Distillation
Martin Ferianc
Miguel R. D. Rodrigues
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164
2
0
19 May 2022
Mitigating Neural Network Overconfidence with Logit Normalization
Mitigating Neural Network Overconfidence with Logit NormalizationInternational Conference on Machine Learning (ICML), 2022
Jianguo Huang
Renchunzi Xie
Hao-Ran Cheng
Lei Feng
Bo An
Shouqing Yang
OODD
621
347
0
19 May 2022
Extensible Machine Learning for Encrypted Network Traffic Application
  Labeling via Uncertainty Quantification
Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty QuantificationIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022
Steven Jorgensen
J. Holodnak
Jensen Dempsey
Karla de Souza
Ananditha Raghunath
Vernon Rivet
N. Demoes
Andrés Alejos
Allan B. Wollaber
AAML
220
48
0
11 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-AwarenessJournal of machine learning research (JMLR), 2022
J. Liu
Shreyas Padhy
Jie Jessie Ren
Zi Lin
Yeming Wen
Ghassen Jerfel
Zachary Nado
Jasper Snoek
Dustin Tran
Balaji Lakshminarayanan
UQCVBDL
489
66
0
01 May 2022
Tailored Uncertainty Estimation for Deep Learning Systems
Tailored Uncertainty Estimation for Deep Learning Systems
Joachim Sicking
Maram Akila
Jan David Schneider
Fabian Hüger
Peter Schlicht
Tim Wirtz
Stefan Wrobel
UQCV
167
2
0
29 Apr 2022
Trusted Multi-View Classification with Dynamic Evidential Fusion
Trusted Multi-View Classification with Dynamic Evidential FusionIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Zongbo Han
Changqing Zhang
Huazhu Fu
Qiufeng Wang
EDL
304
353
0
25 Apr 2022
Anomaly Detection in Autonomous Driving: A Survey
Anomaly Detection in Autonomous Driving: A Survey
Daniel Bogdoll
Maximilian Nitsche
J. Marius Zöllner
199
164
0
17 Apr 2022
Out-of-Distribution Detection with Deep Nearest Neighbors
Out-of-Distribution Detection with Deep Nearest NeighborsInternational Conference on Machine Learning (ICML), 2022
Yiyou Sun
Yifei Ming
Xiaojin Zhu
Shouqing Yang
OODD
576
685
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-LossNeural Processing Letters (NPL), 2022
Qiuyu Zhu
Guohui Zheng
Yingying Yan
OODD
157
8
0
10 Apr 2022
Discovering and forecasting extreme events via active learning in neural
  operators
Discovering and forecasting extreme events via active learning in neural operatorsNature Computational Science (Nat. Comput. Sci.), 2022
Ethan Pickering
Stephen Guth
George Karniadakis
T. Sapsis
AI4CE
231
73
0
05 Apr 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian
  Classification
On Uncertainty, Tempering, and Data Augmentation in Bayesian ClassificationNeural Information Processing Systems (NeurIPS), 2022
Sanyam Kapoor
Wesley J. Maddox
Pavel Izmailov
A. Wilson
BDLUD
248
58
0
30 Mar 2022
Expanding Low-Density Latent Regions for Open-Set Object Detection
Expanding Low-Density Latent Regions for Open-Set Object DetectionComputer Vision and Pattern Recognition (CVPR), 2022
Jiaming Han
Yuqiang Ren
Jian Ding
Xingjia Pan
Ke Yan
Guisong Xia
ObjD
276
79
0
28 Mar 2022
Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty
  Quantification
Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty QuantificationEuropean Conference on Computer Vision (ECCV), 2022
Jianxiong Shen
Antonio Agudo
Francesc Moreno-Noguer
Adria Ruiz
AI4CE
268
73
0
18 Mar 2022
Self-Distribution Distillation: Efficient Uncertainty Estimation
Self-Distribution Distillation: Efficient Uncertainty EstimationConference on Uncertainty in Artificial Intelligence (UAI), 2022
Yassir Fathullah
Mark Gales
UQCV
147
11
0
15 Mar 2022
Pitfalls of Epistemic Uncertainty Quantification through Loss
  Minimisation
Pitfalls of Epistemic Uncertainty Quantification through Loss MinimisationNeural Information Processing Systems (NeurIPS), 2022
Viktor Bengs
Eyke Hüllermeier
Willem Waegeman
EDLUQCVUD
320
53
0
11 Mar 2022
Estimating the Uncertainty in Emotion Class Labels with
  Utterance-Specific Dirichlet Priors
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet PriorsIEEE Transactions on Affective Computing (IEEE TAC), 2022
Wen Wu
Chuxu Zhang
Xixin Wu
P. Woodland
296
17
0
08 Mar 2022
Layer Adaptive Deep Neural Networks for Out-of-distribution Detection
Layer Adaptive Deep Neural Networks for Out-of-distribution DetectionPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022
Haoliang Wang
Chengli Zhao
Xujiang Zhao
Feng Chen
OODD
151
7
0
01 Mar 2022
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification
  with Rejection from ECG Recordings
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification with Rejection from ECG Recordings
Wen-Rang Zhang
Xinxin Di
Guodong Wei
Shijia Geng
Zhaoji Fu
linda Qiao
UQCVBDL
84
2
0
26 Feb 2022
Deep Ensembles Work, But Are They Necessary?
Deep Ensembles Work, But Are They Necessary?Neural Information Processing Systems (NeurIPS), 2022
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
R. Zemel
John P. Cunningham
OODUQCV
353
79
0
14 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
238
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
187
43
0
07 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Deebul Nair
Nico Hochgeschwender
Miguel A. Olivares-Mendez
OOD
235
9
0
03 Feb 2022
SoftDropConnect (SDC) -- Effective and Efficient Quantification of the
  Network Uncertainty in Deep MR Image Analysis
SoftDropConnect (SDC) -- Effective and Efficient Quantification of the Network Uncertainty in Deep MR Image Analysis
Qing Lyu
C. Whitlow
Ge Wang
UQCVBDL
202
2
0
20 Jan 2022
Invariant Representation Driven Neural Classifier for Anti-QCD Jet
  Tagging
Invariant Representation Driven Neural Classifier for Anti-QCD Jet TaggingJournal of High Energy Physics (JHEP), 2022
Taoli Cheng
Aaron Courville
332
6
0
18 Jan 2022
Robust uncertainty estimates with out-of-distribution pseudo-inputs
  training
Robust uncertainty estimates with out-of-distribution pseudo-inputs training
Pierre Segonne
Yevgen Zainchkovskyy
Søren Hauberg
UQCVOOD
122
1
0
15 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
363
15
0
23 Dec 2021
Improving evidential deep learning via multi-task learning
Improving evidential deep learning via multi-task learning
Dongpin Oh
Bonggun Shin
EDLUQCV
227
31
0
17 Dec 2021
Provable Guarantees for Understanding Out-of-distribution Detection
Provable Guarantees for Understanding Out-of-distribution Detection
Peyman Morteza
Shouqing Yang
OODD
227
102
0
01 Dec 2021
Uncertainty Aware Proposal Segmentation for Unknown Object Detection
Uncertainty Aware Proposal Segmentation for Unknown Object Detection
Yimeng Li
Jana Kosecka
UQCV
214
21
0
25 Nov 2021
Consensus Synergizes with Memory: A Simple Approach for Anomaly
  Segmentation in Urban Scenes
Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes
Jiazhong Cen
Zekun Jiang
Lingxi Xie
Qi Tian
Dongsheng Jiang
Wei Shen
224
6
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
495
111
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
414
201
0
18 Nov 2021
Combating Noise: Semi-supervised Learning by Region Uncertainty
  Quantification
Combating Noise: Semi-supervised Learning by Region Uncertainty QuantificationNeural Information Processing Systems (NeurIPS), 2021
Zhenyu Wang
Yali Li
Ye Guo
Shengjin Wang
NoLa
129
31
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01 Nov 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
686
223
0
26 Oct 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift
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Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park
Anas Awadalla
Tadayoshi Kohno
Shwetak N. Patel
OOD
179
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Graph Posterior Network: Bayesian Predictive Uncertainty for Node
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Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
UQCVBDL
325
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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
772
1,223
0
21 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
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167
28
0
18 Oct 2021
Identifying Incorrect Classifications with Balanced Uncertainty
Identifying Incorrect Classifications with Balanced Uncertainty
Bolian Li
Zige Zheng
Changqing Zhang
UQCV
151
3
0
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Dense Uncertainty Estimation
Dense Uncertainty Estimation
Jing Zhang
Yuchao Dai
Mochu Xiang
Deng-Ping Fan
Peyman Moghadam
Mingyi He
Christian J. Walder
Kaihao Zhang
Mehrtash Harandi
Nick Barnes
UQCVBDL
305
12
0
13 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning
  Methods For Uncertainty Estimation
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation
Dennis Ulmer
Christian Hardmeier
J. Frellsen
BDLUQCVUDEDLPER
335
78
0
06 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness
Deep Classifiers with Label Noise Modeling and Distance Awareness
Vincent Fortuin
Mark Collier
F. Wenzel
J. Allingham
J. Liu
Dustin Tran
Balaji Lakshminarayanan
Jesse Berent
Rodolphe Jenatton
E. Kokiopoulou
UQCV
267
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0
06 Oct 2021
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video
  Prediction
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction
Moitreya Chatterjee
Narendra Ahuja
A. Cherian
UQCVVGenBDL
259
18
0
06 Oct 2021
$f$-Cal: Calibrated aleatoric uncertainty estimation from neural
  networks for robot perception
fff-Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception
Dhaivat Bhatt
Kaustubh Mani
Dishank Bansal
Krishna Murthy Jatavallabhula
Hanju Lee
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243
6
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DEBOSH: Deep Bayesian Shape Optimization
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Artem Lukoyanov
Jonathan Donier
Pascal Fua
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185
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A Physics inspired Functional Operator for Model Uncertainty
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A Physics inspired Functional Operator for Model Uncertainty Quantification in the RKHS
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232
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SoK: Machine Learning Governance
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Uncertainty Measures in Neural Belief Tracking and the Effects on
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Revealing the Distributional Vulnerability of Discriminators by Implicit
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