On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks

27 May 2019

Papers citing "On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks"

50 / 136 papers shown

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 157 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
Uncertainty Quantification Metrics for Deep Regression Simon Kristoffersson Lind Ziliang Xiong Per-Erik Forssén Volker Kruger UQCV 32 3 0 07 May 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 21 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 23 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 11 0 27 Jan 2023
Uncertainty Estimation based on Geometric Separation Gabriella Chouraqui L. Cohen Gil Einziger Liel Leman 33 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
Block Selection Method for Using Feature Norm in Out-of-distribution Detection Yeonguk Yu Sungho Shin Seongju Lee C. Jun Kyoobin Lee OODD 25 31 0 05 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 37 13 0 10 Nov 2022
Cold Start Streaming Learning for Deep Networks Cameron R. Wolfe Anastasios Kyrillidis CLL 23 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
Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup Muthuraman Chidambaram Xiang Wang Chenwei Wu Rong Ge MLT 11 8 0 24 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