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Measuring Calibration in Deep Learning

Measuring Calibration in Deep Learning

2 April 2019
Jeremy Nixon
Michael W. Dusenberry
Ghassen Jerfel
Timothy Nguyen
Jeremiah Zhe Liu
Linchuan Zhang
Dustin Tran
    UQCV
ArXivPDFHTML

Papers citing "Measuring Calibration in Deep Learning"

50 / 310 papers shown
Title
How To Effectively Train An Ensemble Of Faster R-CNN Object Detectors To
  Quantify Uncertainty
How To Effectively Train An Ensemble Of Faster R-CNN Object Detectors To Quantify Uncertainty
Denis Mbey Akola
Gianni Franchi
ObjD
UQCV
36
0
0
07 Oct 2023
Something for (almost) nothing: Improving deep ensemble calibration
  using unlabeled data
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data
Konstantinos Pitas
Julyan Arbel
BDL
UQCV
FedML
38
0
0
04 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates
A Primer on Bayesian Neural Networks: Review and Debates
Federico Danieli
Konstantinos Pitas
M. Vladimirova
Vincent Fortuin
BDL
AAML
56
18
0
28 Sep 2023
MoCaE: Mixture of Calibrated Experts Significantly Improves Object
  Detection
MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection
Kemal Oksuz
Selim Kuzucu
Tom Joy
P. Dokania
MoE
29
5
0
26 Sep 2023
PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with
  Relation-Aware Score Calibration
PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration
Minseok Choi
Hyesu Lim
Jaegul Choo
32
2
0
25 Sep 2023
Understanding Calibration of Deep Neural Networks for Medical Image
  Classification
Understanding Calibration of Deep Neural Networks for Medical Image Classification
A. Sambyal
Usma Niyaz
N. C. Krishnan
Deepti R. Bathula
19
7
0
22 Sep 2023
Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing
Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing
Jarosław Błasiok
Preetum Nakkiran
UQCV
53
21
0
21 Sep 2023
Rethinking Evaluation Metric for Probability Estimation Models Using
  Esports Data
Rethinking Evaluation Metric for Probability Estimation Models Using Esports Data
Euihyeon Choi
Jooyoung Kim
Wonkyung Lee
33
0
0
12 Sep 2023
Do We Still Need Non-Maximum Suppression? Accurate Confidence Estimates
  and Implicit Duplication Modeling with IoU-Aware Calibration
Do We Still Need Non-Maximum Suppression? Accurate Confidence Estimates and Implicit Duplication Modeling with IoU-Aware Calibration
Johannes Gilg
Torben Teepe
Fabian Herzog
Philipp Wolters
Gerhard Rigoll
18
1
0
06 Sep 2023
Multiclass Alignment of Confidence and Certainty for Network Calibration
Multiclass Alignment of Confidence and Certainty for Network Calibration
Vinith Kugathasan
M. H. Khan
UQCV
22
1
0
06 Sep 2023
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with
  Uncertainty Quantification
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification
Jacopo Talpini
Fabio Sartori
Marco Savi
29
2
0
05 Sep 2023
A Theoretical and Practical Framework for Evaluating Uncertainty
  Calibration in Object Detection
A Theoretical and Practical Framework for Evaluating Uncertainty Calibration in Object Detection
Pedro Conde
Rui L. Lopes
C. Premebida
UQCV
15
1
0
01 Sep 2023
Uncertainty Aware Training to Improve Deep Learning Model Calibration
  for Classification of Cardiac MR Images
Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images
Tareen Dawood
Chen Chen
B. Sidhu
B. Ruijsink
J. Gould
...
Vishal S. Mehta
C. Rinaldi
Esther Puyol-Antón
Reza Razavi
A. King
OOD
30
10
0
29 Aug 2023
Diversified Ensemble of Independent Sub-Networks for Robust
  Self-Supervised Representation Learning
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning
Amirhossein Vahidi
Lisa Wimmer
H. Gündüz
Bernd Bischl
Eyke Hüllermeier
Mina Rezaei
OOD
UQCV
32
4
0
28 Aug 2023
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration
Hyekang Park
Jongyoun Noh
Youngmin Oh
Donghyeon Baek
Bumsub Ham
UQCV
36
12
0
23 Aug 2023
A Benchmark Study on Calibration
A Benchmark Study on Calibration
Linwei Tao
Younan Zhu
Haolan Guo
Minjing Dong
Chang Xu
26
9
0
23 Aug 2023
A Neural Network Based Choice Model for Assortment Optimization
A Neural Network Based Choice Model for Assortment Optimization
Hanrui Wang
Zhongze Cai
Xiaocheng Li
Kalyan Talluri
11
2
0
10 Aug 2023
Expert load matters: operating networks at high accuracy and low manual
  effort
Expert load matters: operating networks at high accuracy and low manual effort
Sara Sangalli
Ertunc Erdil
E. Konukoglu
17
4
0
09 Aug 2023
Two Sides of Miscalibration: Identifying Over and Under-Confidence
  Prediction for Network Calibration
Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration
Shuang Ao
Stefan Rueger
Advaith Siddharthan
UQCV
13
8
0
06 Aug 2023
On the Calibration of Uncertainty Estimation in LiDAR-based Semantic
  Segmentation
On the Calibration of Uncertainty Estimation in LiDAR-based Semantic Segmentation
M. Dreissig
Florian Piewak
Joschka Boedecker
UQCV
23
6
0
04 Aug 2023
Calibration in Deep Learning: A Survey of the State-of-the-Art
Calibration in Deep Learning: A Survey of the State-of-the-Art
Cheng Wang
UQCV
36
37
0
02 Aug 2023
Continuous Time Evidential Distributions for Irregular Time Series
Continuous Time Evidential Distributions for Irregular Time Series
Taylor W. Killian
Haoran Zhang
Thomas Hartvigsen
Ava P. Amini
OOD
EDL
44
0
0
25 Jul 2023
Towards Reliable Rare Category Analysis on Graphs via Individual
  Calibration
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration
Longfeng Wu
Bowen Lei
Dongkuan Xu
Dawei Zhou
UQCV
CML
42
9
0
19 Jul 2023
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration
Hiroki Naganuma
Ryuichiro Hataya
Kotaro Yoshida
Ioannis Mitliagkas
OODD
95
1
0
17 Jul 2023
Boundary-weighted logit consistency improves calibration of segmentation
  networks
Boundary-weighted logit consistency improves calibration of segmentation networks
Neerav Karani
Neel Dey
Polina Golland
30
3
0
16 Jul 2023
Drug Discovery under Covariate Shift with Domain-Informed Prior
  Distributions over Functions
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions
Leo Klarner
Tim G. J. Rudner
M. Reutlinger
Torsten Schindler
Garrett M. Morris
Charlotte M. Deane
Yee Whye Teh
OOD
BDL
15
9
0
14 Jul 2023
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and
  Resolution
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
Mostafa Dehghani
Basil Mustafa
Josip Djolonga
Jonathan Heek
Matthias Minderer
...
Avital Oliver
Piotr Padlewski
A. Gritsenko
Mario Luvcić
N. Houlsby
ViT
31
105
0
12 Jul 2023
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning
Qin Zhang
Linghan Xu
Qingming Tang
Jun Fang
Yingqi Wu
Joseph Tighe
Yifan Xing
27
4
0
08 Jul 2023
Mitigating Calibration Bias Without Fixed Attribute Grouping for
  Improved Fairness in Medical Imaging Analysis
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis
Changjian Shui
Justin Szeto
Raghav Mehta
Douglas L. Arnold
Tal Arbel
11
5
0
04 Jul 2023
Towards Building Self-Aware Object Detectors via Reliable Uncertainty
  Quantification and Calibration
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration
Kemal Oksuz
Thomas Joy
P. Dokania
UQCV
28
16
0
03 Jul 2023
TCE: A Test-Based Approach to Measuring Calibration Error
TCE: A Test-Based Approach to Measuring Calibration Error
Takuo Matsubara
Niek Tax
Richard Mudd
Ido Guy
27
4
0
25 Jun 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep
  Learning under Distribution Shift
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift
Florian Seligmann
P. Becker
Michael Volpp
Gerhard Neumann
UQCV
32
14
0
21 Jun 2023
MiniLLM: Knowledge Distillation of Large Language Models
MiniLLM: Knowledge Distillation of Large Language Models
Yuxian Gu
Li Dong
Furu Wei
Minlie Huang
ALM
44
77
0
14 Jun 2023
Conservative Prediction via Data-Driven Confidence Minimization
Conservative Prediction via Data-Driven Confidence Minimization
Caroline Choi
Fahim Tajwar
Yoonho Lee
Huaxiu Yao
Ananya Kumar
Chelsea Finn
34
5
0
08 Jun 2023
Proximity-Informed Calibration for Deep Neural Networks
Proximity-Informed Calibration for Deep Neural Networks
Miao Xiong
Ailin Deng
Pang Wei Koh
Jiaying Wu
Shen Li
Jianqing Xu
Bryan Hooi
UQCV
29
12
0
07 Jun 2023
Provable Dynamic Fusion for Low-Quality Multimodal Data
Provable Dynamic Fusion for Low-Quality Multimodal Data
Qingyang Zhang
Haitao Wu
Changqing Zhang
Qinghua Hu
Huazhu Fu
Qiufeng Wang
Xi Peng
45
56
0
03 Jun 2023
Quantifying Deep Learning Model Uncertainty in Conformal Prediction
Quantifying Deep Learning Model Uncertainty in Conformal Prediction
Hamed Karimi
Reza Samavi
UQCV
19
9
0
01 Jun 2023
On the Limitations of Temperature Scaling for Distributions with
  Overlaps
On the Limitations of Temperature Scaling for Distributions with Overlaps
Muthuraman Chidambaram
Rong Ge
UQCV
40
4
0
01 Jun 2023
Perception and Semantic Aware Regularization for Sequential Confidence
  Calibration
Perception and Semantic Aware Regularization for Sequential Confidence Calibration
Zhenghua Peng
Yuanmao Luo
Tianshui Chen
Keke Xu
Shuangping Huang
AI4TS
35
2
0
31 May 2023
Generating with Confidence: Uncertainty Quantification for Black-box
  Large Language Models
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
Zhen Lin
Shubhendu Trivedi
Jimeng Sun
HILM
29
130
0
30 May 2023
Trustworthy Sensor Fusion against Inaudible Command Attacks in Advanced
  Driver-Assistance System
Trustworthy Sensor Fusion against Inaudible Command Attacks in Advanced Driver-Assistance System
Jiwei Guan
Lei Pan
Chen Wang
Shui Yu
Longxiang Gao
Xi Zheng
AAML
24
3
0
30 May 2023
Calibration of Transformer-based Models for Identifying Stress and
  Depression in Social Media
Calibration of Transformer-based Models for Identifying Stress and Depression in Social Media
Loukas Ilias
S. Mouzakitis
D. Askounis
33
41
0
26 May 2023
Context-aware attention layers coupled with optimal transport domain
  adaptation and multimodal fusion methods for recognizing dementia from
  spontaneous speech
Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speech
Loukas Ilias
D. Askounis
34
9
0
25 May 2023
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Xiaohui Chen
Jiankai Sun
Taiqing Wang
Ruocheng Guo
Liping Liu
Aonan Zhang
32
3
0
25 May 2023
Dual Focal Loss for Calibration
Dual Focal Loss for Calibration
Linwei Tao
Minjing Dong
Chang Xu
UQCV
52
26
0
23 May 2023
Document Understanding Dataset and Evaluation (DUDE)
Document Understanding Dataset and Evaluation (DUDE)
Jordy Van Landeghem
Rubèn Pérez Tito
Łukasz Borchmann
Michal Pietruszka
Pawel Józiak
...
Bertrand Ackaert
Ernest Valveny
Matthew Blaschko
Sien Moens
Tomasz Stanislawek
VGen
24
53
0
15 May 2023
Calibration Error Estimation Using Fuzzy Binning
Calibration Error Estimation Using Fuzzy Binning
Geetanjali Bihani
Julia Taylor Rayz
105
2
0
30 Apr 2023
Coarse race data conceals disparities in clinical risk score performance
Coarse race data conceals disparities in clinical risk score performance
Rajiv Movva
Divya Shanmugam
Kaihua Hou
P. Pathak
John Guttag
Nikhil Garg
Emma Pierson
16
17
0
18 Apr 2023
Transfer Knowledge from Head to Tail: Uncertainty Calibration under
  Long-tailed Distribution
Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution
Jiahao Chen
Bingyue Su
32
11
0
13 Apr 2023
Approaching Test Time Augmentation in the Context of Uncertainty
  Calibration for Deep Neural Networks
Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural Networks
Pedro Conde
T. Barros
Rui L. Lopes
C. Premebida
U. J. Nunes
UQCV
32
7
0
11 Apr 2023
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