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A Review of Uncertainty Quantification in Deep Learning: Techniques,
  Applications and Challenges

A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

12 November 2020
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Li Liu
Mohammad Ghavamzadeh
Paul Fieguth
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
    BDL
    UQCV
ArXivPDFHTML

Papers citing "A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges"

50 / 159 papers shown
Title
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results
Meritxell Riera-Marin
S. Ko
Julia Rodriguez-Comas
Matthias Stefan May
Zhaohong Pan
...
Anton Aubanell
Andreu Antolin
Javier Garcia-Lopez
M. A. G. Ballester
Adrian Galdran
UQCV
36
0
0
13 May 2025
Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties
Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties
Jiaxiang Yi
Miguel A. Bessa
UD
PER
UQCV
39
0
0
05 May 2025
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion
Aurelio Raffa Ugolini
M. Tanelli
Valentina Breschi
MoE
21
0
0
02 May 2025
Geometry-Informed Neural Operator Transformer
Geometry-Informed Neural Operator Transformer
Qibang Liu
Vincient Zhong
Hadi Meidani
Diab Abueidda
S. Koric
Philippe Geubelle
AI4CE
44
0
0
28 Apr 2025
Introducing Interval Neural Networks for Uncertainty-Aware System Identification
Introducing Interval Neural Networks for Uncertainty-Aware System Identification
Mehmet Ali Ferah
Tufan Kumbasar
19
0
0
26 Apr 2025
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
Mohaddeseh Chegini
Ali Mahloojifar
BDL
UQCV
71
0
0
23 Apr 2025
Localization Meets Uncertainty: Uncertainty-Aware Multi-Modal Localization
Localization Meets Uncertainty: Uncertainty-Aware Multi-Modal Localization
Hye-Min Won
Jieun Lee
Jiyong Oh
EDL
49
0
0
10 Apr 2025
Engineering Artificial Intelligence: Framework, Challenges, and Future Direction
Engineering Artificial Intelligence: Framework, Challenges, and Future Direction
Jay Lee
Hanqi Su
Dai-Yan Ji
Takanobu Minami
AI4CE
46
0
0
03 Apr 2025
Uncertainty propagation in feed-forward neural network models
Uncertainty propagation in feed-forward neural network models
Jeremy Diamzon
Daniele Venturi
57
0
0
27 Mar 2025
BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning model
BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning model
Mohaddeseh Chegini
Ali Mahloojifar
61
1
0
18 Mar 2025
MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration
MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration
Siguang Huang
Yunli Wang
Lili Mou
Huayue Zhang
Han Zhu
Chuan Yu
Bo Zheng
48
15
0
13 Mar 2025
Conformal Prediction with Upper and Lower Bound Models
Miao Li
Michael Klamkin
Mathieu Tanneau
Reza Zandehshahvar
Pascal Van Hentenryck
48
0
0
06 Mar 2025
Uncertainty-Aware Graph Structure Learning
Uncertainty-Aware Graph Structure Learning
Shen Han
Zhiyao Zhou
Jiawei Chen
Zhezheng Hao
Sheng Zhou
Gang Wang
Yan Feng
C. L. P. Chen
C. Wang
43
2
0
20 Feb 2025
Conformal Prediction Sets Can Cause Disparate Impact
Conformal Prediction Sets Can Cause Disparate Impact
Jesse C. Cresswell
Bhargava Kumar
Yi Sui
Mouloud Belbahri
FaML
77
1
0
17 Feb 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
Kaizheng Wang
Keivan K1 Shariatmadar
Shireen Kudukkil Manchingal
Fabio Cuzzolin
David Moens
Hans Hallez
UQCV
BDL
80
12
0
28 Jan 2025
Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning
Jiang Chang
Deekshith Basvoju
Aleksandar Vakanski
Indrajit Charit
Min Xian
AI4CE
32
0
0
28 Jan 2025
Evolution and The Knightian Blindspot of Machine Learning
Evolution and The Knightian Blindspot of Machine Learning
Joel Lehman
Elliot Meyerson
Tarek El-Gaaly
Kenneth O. Stanley
Tarin Ziyaee
81
1
0
22 Jan 2025
Uncertainty and Energy based Loss Guided Semi-Supervised Semantic Segmentation
Uncertainty and Energy based Loss Guided Semi-Supervised Semantic Segmentation
Rini Smita Thakur
Vinod K. Kurmi
UQCV
29
1
0
03 Jan 2025
Confidence Calibration of Classifiers with Many Classes
Confidence Calibration of Classifiers with Many Classes
Adrien LeCoz
Stéphane Herbin
Faouzi Adjed
UQCV
33
1
0
05 Nov 2024
A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators
A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators
Han Zhou
Jordy Van Landeghem
Teodora Popordanoska
Matthew B. Blaschko
30
0
0
20 Oct 2024
Lightning UQ Box: A Comprehensive Framework for Uncertainty
  Quantification in Deep Learning
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
Nils Lehmann
Jakob Gawlikowski
Adam J. Stewart
Vytautas Jancauskas
Stefan Depeweg
Eric T. Nalisnick
N. Gottschling
35
0
0
04 Oct 2024
Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown
Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown
Xingzhou Lou
Dong Yan
Wei Shen
Yuzi Yan
Jian Xie
Junge Zhang
45
21
0
01 Oct 2024
Trust-informed Decision-Making Through An Uncertainty-Aware Stacked
  Neural Networks Framework: Case Study in COVID-19 Classification
Trust-informed Decision-Making Through An Uncertainty-Aware Stacked Neural Networks Framework: Case Study in COVID-19 Classification
Hassan Gharoun
M. S. Khorshidi
Fang Chen
Amir H. Gandomi
23
0
0
19 Sep 2024
DDEvENet: Evidence-based Ensemble Learning for Uncertainty-aware Brain Parcellation Using Diffusion MRI
DDEvENet: Evidence-based Ensemble Learning for Uncertainty-aware Brain Parcellation Using Diffusion MRI
Chenjun Li
Dian Yang
Shun Yao
Shuyue Wang
Ye Wu
...
C. Westin
L. O’Donnell
N. Sochen
O. Pasternak
Fan Zhang
UQCV
32
0
0
11 Sep 2024
SEF: A Method for Computing Prediction Intervals by Shifting the Error
  Function in Neural Networks
SEF: A Method for Computing Prediction Intervals by Shifting the Error Function in Neural Networks
E. V. Aretos
D. G. Sotiropoulos
16
0
0
08 Sep 2024
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended
  Text Generation
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation
Esteban Garces Arias
Julian Rodemann
Meimingwei Li
Christian Heumann
Matthias Aßenmacher
27
3
0
26 Jul 2024
SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and
  Active Sensing
SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing
Changchang Yin
Ruoqi Liu
Bingsheng Yao
Dongdong Zhang
Jeffrey Caterino
Ping Zhang
27
42
0
24 Jul 2024
Risks of uncertainty propagation in Al-augmented security pipelines
Risks of uncertainty propagation in Al-augmented security pipelines
Emanuele Mezzi
Aurora Papotti
Fabio Massacci
Katja Tuma
25
0
0
14 Jul 2024
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
Shihua Sun
Shridatt Sugrim
Angelos Stavrou
Haining Wang
AAML
44
1
0
13 Jul 2024
Combine and Conquer: A Meta-Analysis on Data Shift and
  Out-of-Distribution Detection
Combine and Conquer: A Meta-Analysis on Data Shift and Out-of-Distribution Detection
Eduardo Dadalto
F. Alberge
Pierre Duhamel
Pablo Piantanida
OODD
39
0
0
23 Jun 2024
Trustworthy Enhanced Multi-view Multi-modal Alzheimer's Disease Prediction with Brain-wide Imaging Transcriptomics Data
Trustworthy Enhanced Multi-view Multi-modal Alzheimer's Disease Prediction with Brain-wide Imaging Transcriptomics Data
Shan Cong
Zhoujie Fan
Hongwei Liu
Yinghan Zhang
Xin Wang
Haoran Luo
Xiaohui Yao
18
1
0
21 Jun 2024
Cycles of Thought: Measuring LLM Confidence through Stable Explanations
Cycles of Thought: Measuring LLM Confidence through Stable Explanations
Evan Becker
Stefano Soatto
35
6
0
05 Jun 2024
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of
  LLMs
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMs
Shuang Ao
Stefan Rueger
Advaith Siddharthan
28
1
0
05 Jun 2024
CONFINE: Conformal Prediction for Interpretable Neural Networks
CONFINE: Conformal Prediction for Interpretable Neural Networks
Linhui Huang
S. Lala
N. Jha
63
2
0
01 Jun 2024
Towards Better Understanding of In-Context Learning Ability from
  In-Context Uncertainty Quantification
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
Shang Liu
Zhongze Cai
Guanting Chen
Xiaocheng Li
UQCV
38
1
0
24 May 2024
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde
Francesco Pinto
Thomas Lukasiewicz
Philip H. S. Torr
Adel Bibi
AAML
33
0
0
22 May 2024
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification
Ruben Grewal
Paolo Tonella
Andrea Stocco
40
10
0
29 Apr 2024
Machine Learning-Guided Design of Non-Reciprocal and Asymmetric Elastic
  Chiral Metamaterials
Machine Learning-Guided Design of Non-Reciprocal and Asymmetric Elastic Chiral Metamaterials
Lingxiao Yuan
Emma Lejeune
Harold S. Park
23
0
0
19 Apr 2024
Enhancing Interval Type-2 Fuzzy Logic Systems: Learning for Precision
  and Prediction Intervals
Enhancing Interval Type-2 Fuzzy Logic Systems: Learning for Precision and Prediction Intervals
Ata Koklu
Yusuf Guven
T. Kumbasar
20
2
0
19 Apr 2024
From Robustness to Improved Generalization and Calibration in
  Pre-trained Language Models
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models
Josip Jukić
Jan Snajder
21
0
0
31 Mar 2024
Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding
Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding
Lingdong Kong
Xiang Xu
Jun Cen
Wenwei Zhang
Liang Pan
Kai-xiang Chen
Ziwei Liu
45
5
0
25 Mar 2024
What Matters for Active Texture Recognition With Vision-Based Tactile
  Sensors
What Matters for Active Texture Recognition With Vision-Based Tactile Sensors
Alina Böhm
Tim Schneider
Boris Belousov
Alap Kshirsagar
L. P. Y. Lin
Katja Doerschner
K. Drewing
Constantin Rothkopf
Jan Peters
20
6
0
20 Mar 2024
Uncertainty in Graph Neural Networks: A Survey
Uncertainty in Graph Neural Networks: A Survey
Fangxin Wang
Yuqing Liu
Kay Liu
Yibo Wang
Sourav Medya
Philip S. Yu
AI4CE
46
8
0
11 Mar 2024
Scalable Bayesian inference for the generalized linear mixed model
Scalable Bayesian inference for the generalized linear mixed model
S. Berchuck
Felipe A. Medeiros
Sayan Mukherjee
Andrea Agazzi
24
0
0
05 Mar 2024
Towards Safe and Reliable Autonomous Driving: Dynamic Occupancy Set
  Prediction
Towards Safe and Reliable Autonomous Driving: Dynamic Occupancy Set Prediction
Wenbo Shao
Jiahui Xu
Wenhao Yu
Jun Li
Hong Wang
33
1
0
29 Feb 2024
Artificial Bee Colony optimization of Deep Convolutional Neural Networks
  in the context of Biomedical Imaging
Artificial Bee Colony optimization of Deep Convolutional Neural Networks in the context of Biomedical Imaging
Adri Gomez Martin
Carlos Fernandez del Cerro
Monica Abella Garcia
Manuel Desco Menendez
21
0
0
23 Feb 2024
Uncertainty estimates for semantic segmentation: providing enhanced
  reliability for automated motor claims handling
Uncertainty estimates for semantic segmentation: providing enhanced reliability for automated motor claims handling
Jan Küchler
Daniel Kröll
S. Schoenen
Andreas Witte
UQCV
32
1
0
17 Jan 2024
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation
S. Chatterjee
Franziska Gaidzik
Alessandro Sciarra
Hendrik Mattern
G. Janiga
Oliver Speck
Andreas Nürnberger
S. Pathiraja
33
0
0
25 Dec 2023
Identifying Drivers of Predictive Aleatoric Uncertainty
Identifying Drivers of Predictive Aleatoric Uncertainty
Pascal Iversen
Simon Witzke
Katharina Baum
Bernhard Y. Renard
UD
43
1
0
12 Dec 2023
A Stochastic-Geometrical Framework for Object Pose Estimation based on
  Mixture Models Avoiding the Correspondence Problem
A Stochastic-Geometrical Framework for Object Pose Estimation based on Mixture Models Avoiding the Correspondence Problem
Wolfgang Hoegele
16
2
0
29 Nov 2023
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