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1905.11001
Cited By
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
27 May 2019
S. Thulasidasan
Gopinath Chennupati
J. Bilmes
Tanmoy Bhattacharya
S. Michalak
UQCV
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Papers citing
"On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks"
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Title
MIDAS: Mixing Ambiguous Data with Soft Labels for Dynamic Facial Expression Recognition
Ryosuke Kawamura
Hideaki Hayashi
Noriko Takemura
Hajime Nagahara
CVBM
3DH
65
4
0
28 Feb 2025
Technical report on label-informed logit redistribution for better domain generalization in low-shot classification with foundation models
Behraj Khan
T. Syed
148
1
0
29 Jan 2025
Fine-Grained Uncertainty Quantification via Collisions
Jesse Friedbaum
Sudarshan Adiga
Ravi Tandon
69
0
0
18 Nov 2024
Confidence Calibration of Classifiers with Many Classes
Adrien LeCoz
Stéphane Herbin
Faouzi Adjed
UQCV
37
1
0
05 Nov 2024
CALICO: Confident Active Learning with Integrated Calibration
L. S. Querol
Hajime Nagahara
Hideaki Hayashi
28
0
0
02 Jul 2024
Reassessing How to Compare and Improve the Calibration of Machine Learning Models
M. Chidambaram
Rong Ge
74
1
0
06 Jun 2024
Orthogonal Causal Calibration
Justin Whitehouse
Christopher Jung
Vasilis Syrgkanis
Bryan Wilder
Zhiwei Steven Wu
CML
114
1
0
04 Jun 2024
Robust Classification by Coupling Data Mollification with Label Smoothing
Markus Heinonen
Ba-Hien Tran
Michael Kampffmeyer
Maurizio Filippone
73
0
0
03 Jun 2024
Class and Region-Adaptive Constraints for Network Calibration
Balamurali Murugesan
Julio Silva-Rodríguez
Ismail Ben Ayed
Jose Dolz
36
1
0
19 Mar 2024
Revisiting Confidence Estimation: Towards Reliable Failure Prediction
Fei Zhu
Xu-Yao Zhang
Zhen Cheng
Cheng-Lin Liu
UQCV
52
10
0
05 Mar 2024
Calibration of Deep Learning Classification Models in fNIRS
Zhihao Cao
Zizhou Luo
38
1
0
23 Feb 2024
Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration
Wonjeong Choi
Jun-Gyu Park
Dong-Jun Han
Younghyun Park
Jaekyun Moon
45
1
0
22 Feb 2024
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex
Yasushi Esaki
Akihiro Nakamura
Keisuke Kawano
Ryoko Tokuhisa
Takuro Kutsuna
46
0
0
21 Feb 2024
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation
Muthuraman Chidambaram
Rong Ge
AAML
18
0
0
10 Feb 2024
Pushing Boundaries: Mixup's Influence on Neural Collapse
Quinn Fisher
Haoming Meng
Vardan Papyan
AAML
UQCV
44
5
0
09 Feb 2024
Learning Shortcuts: On the Misleading Promise of NLU in Language Models
Geetanjali Bihani
Julia Taylor Rayz
33
3
0
17 Jan 2024
Single-channel speech enhancement using learnable loss mixup
Oscar Chang
Dung N. Tran
K. Koishida
48
7
0
20 Dec 2023
STEM Rebalance: A Novel Approach for Tackling Imbalanced Datasets using SMOTE, Edited Nearest Neighbour, and Mixup
Yumnah Hasan
Fatemeh Amerehi
Patrick Healy
Conor Ryan
20
4
0
13 Nov 2023
Tailoring Mixup to Data for Calibration
Quentin Bouniot
Pavlo Mozharovskyi
Florence dÁlché-Buc
61
1
0
02 Nov 2023
Model Calibration in Dense Classification with Adaptive Label Perturbation
Jiawei Liu
Changkun Ye
Shanpeng Wang
Rui-Qing Cui
Jing Zhang
Kai Zhang
Nick Barnes
47
5
0
25 Jul 2023
Rethinking Data Distillation: Do Not Overlook Calibration
Dongyao Zhu
Bowen Lei
Jie M. Zhang
Yanbo Fang
Ruqi Zhang
Yiqun Xie
Dongkuan Xu
DD
FedML
23
15
0
24 Jul 2023
Set Learning for Accurate and Calibrated Models
Lukas Muttenthaler
Robert A. Vandermeulen
Qiuyi Zhang
Thomas Unterthiner
Klaus-Robert Muller
34
2
0
05 Jul 2023
Open Set Relation Extraction via Unknown-Aware Training
Jun Zhao
Xin Zhao
Wenyu Zhan
Qi Zhang
Tao Gui
Zhongyu Wei
Yunwen Chen
Xiang Gao
Xuanjing Huang
30
1
0
08 Jun 2023
On the Limitations of Temperature Scaling for Distributions with Overlaps
Muthuraman Chidambaram
Rong Ge
UQCV
37
4
0
01 Jun 2023
Dual Focal Loss for Calibration
Linwei Tao
Minjing Dong
Chang Xu
UQCV
47
26
0
23 May 2023
Infinite Class Mixup
Thomas Mensink
Pascal Mettes
29
2
0
17 May 2023
Calibration Error Estimation Using Fuzzy Binning
Geetanjali Bihani
Julia Taylor Rayz
97
2
0
30 Apr 2023
Adaptive Modeling of Uncertainties for Traffic Forecasting
Ying Wu
Yongchao Ye
Adnan Zeb
James J. Q. Yu
Zihan Wang
AI4TS
24
7
0
16 Mar 2023
Rethinking Confidence Calibration for Failure Prediction
Fei Zhu
Zhen Cheng
Xu-Yao Zhang
Cheng-Lin Liu
UQCV
22
39
0
06 Mar 2023
Distilling Calibrated Student from an Uncalibrated Teacher
Ishan Mishra
Sethu Vamsi Krishna
Deepak Mishra
FedML
40
2
0
22 Feb 2023
Calibrating a Deep Neural Network with Its Predecessors
Linwei Tao
Minjing Dong
Daochang Liu
Changming Sun
Chang Xu
BDL
UQCV
14
5
0
13 Feb 2023
Beyond In-Domain Scenarios: Robust Density-Aware Calibration
Christian Tomani
Futa Waseda
Yuesong Shen
Daniel Cremers
UQCV
34
4
0
10 Feb 2023
Rethinking Soft Label in Label Distribution Learning Perspective
Seungbum Hong
Jihun Yoon
Bogyu Park
Min-Kook Choi
31
0
0
31 Jan 2023
Towards Inference Efficient Deep Ensemble Learning
Ziyue Li
Kan Ren
Yifan Yang
Xinyang Jiang
Yuqing Yang
Dongsheng Li
BDL
26
12
0
29 Jan 2023
Conformal inference is (almost) free for neural networks trained with early stopping
Zi-Chen Liang
Yan Zhou
Matteo Sesia
BDL
18
10
0
27 Jan 2023
Uncertainty Estimation based on Geometric Separation
Gabriella Chouraqui
L. Cohen
Gil Einziger
Liel Leman
30
0
0
11 Jan 2023
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks
Erdong Guo
D. Draper
Maria de Iorio
35
0
0
27 Dec 2022
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability
Chengtai Cao
Fan Zhou
Yurou Dai
Jianping Wang
Kunpeng Zhang
AAML
24
28
0
21 Dec 2022
Rethinking Out-of-Distribution Detection From a Human-Centric Perspective
Yao Zhu
YueFeng Chen
Xiaodan Li
Rong Zhang
Hui Xue
Xiang Tian
Rongxin Jiang
Bo Zheng
Yao-wu Chen
OODD
30
7
0
30 Nov 2022
On Robust Learning from Noisy Labels: A Permutation Layer Approach
Salman Alsubaihi
Mohammed Alkhrashi
Raied Aljadaany
Fahad Albalawi
Guohao Li
NoLa
23
0
0
29 Nov 2022
LUMix: Improving Mixup by Better Modelling Label Uncertainty
Shuyang Sun
Jieneng Chen
Ruifei He
Alan Yuille
Philip Torr
Song Bai
UQCV
NoLa
21
5
0
29 Nov 2022
Layer-Stack Temperature Scaling
Amr Khalifa
Michael C. Mozer
Hanie Sedghi
Behnam Neyshabur
Ibrahim M. Alabdulmohsin
78
2
0
18 Nov 2022
MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis
M. Gadermayr
Lukas Koller
M. Tschuchnig
Lea Maria Stangassinger
Christina Kreutzer
S. Couillard-Després
G. Oostingh
Anton Hittmair
34
13
0
10 Nov 2022
Cold Start Streaming Learning for Deep Networks
Cameron R. Wolfe
Anastasios Kyrillidis
CLL
20
2
0
09 Nov 2022
When does mixup promote local linearity in learned representations?
Arslan Chaudhry
A. Menon
Andreas Veit
Sadeep Jayasumana
Srikumar Ramalingam
Surinder Kumar
28
1
0
28 Oct 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
Dennis Ulmer
J. Frellsen
Christian Hardmeier
189
22
0
20 Oct 2022
Stability of Accuracy for the Training of DNNs Via the Uniform Doubling Condition
Yitzchak Shmalo
28
1
0
16 Oct 2022
CROWDLAB: Supervised learning to infer consensus labels and quality scores for data with multiple annotators
Hui Wen Goh
Ulyana Tkachenko
Jonas W. Mueller
19
10
0
13 Oct 2022
Robust Models are less Over-Confident
Julia Grabinski
Paul Gavrikov
J. Keuper
M. Keuper
AAML
36
24
0
12 Oct 2022
Curved Representation Space of Vision Transformers
Juyeop Kim
Junha Park
Songkuk Kim
Jongseok Lee
ViT
38
6
0
11 Oct 2022
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