Combining Ensembles and Data Augmentation can Harm your Calibration

Combining Ensembles and Data Augmentation can Harm your Calibration

19 October 2020

Michael W. Dusenberry

Balaji Lakshminarayanan

Papers citing "Combining Ensembles and Data Augmentation can Harm your Calibration"

17 / 17 papers shown

Title
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 105 0 0 14 Mar 2025
RegMixMatch: Optimizing Mixup Utilization in Semi-Supervised Learning Haorong Han Jidong Yuan Chixuan Wei Zhongyang Yu 131 1 0 14 Dec 2024
Reassessing How to Compare and Improve the Calibration of Machine Learning Models M. Chidambaram Rong Ge 63 1 0 06 Jun 2024
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods A. Mumuni F. Mumuni 60 4 0 13 Mar 2024
Revisiting Confidence Estimation: Towards Reliable Failure Prediction Fei Zhu Xu-Yao Zhang Zhen Cheng Cheng-Lin Liu UQCV 44 10 0 05 Mar 2024
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 53 1 0 02 Nov 2023
On the Limitations of Temperature Scaling for Distributions with Overlaps Muthuraman Chidambaram Rong Ge UQCV 24 4 0 01 Jun 2023
Rethinking Confidence Calibration for Failure Prediction Fei Zhu Zhen Cheng Xu-Yao Zhang Cheng-Lin Liu UQCV 14 39 0 06 Mar 2023
Curved Representation Space of Vision Transformers Juyeop Kim Junha Park Songkuk Kim Jongseok Lee ViT 28 6 0 11 Oct 2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness Francesco Pinto Harry Yang Ser-Nam Lim Philip H. S. Torr P. Dokania UQCV 25 34 0 29 Jun 2022
How Do Vision Transformers Work? Namuk Park Songkuk Kim ViT 25 463 0 14 Feb 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 30 1,108 0 07 Jul 2021
Correlated Input-Dependent Label Noise in Large-Scale Image Classification Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent NoLa 176 53 0 19 May 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Y. Zou UQCV 20 67 0 11 Feb 2021
Estimating Example Difficulty Using Variance of Gradients Chirag Agarwal Daniel D'souza Sara Hooker 195 105 0 26 Aug 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015