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"

36 / 136 papers shown

Title
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems Shohei Enomoto Takeharu Eda UQCV 46 17 0 15 Apr 2021
Improving Calibration for Long-Tailed Recognition Zhisheng Zhong Jiequan Cui Shu Liu Jiaya Jia 21 288 0 01 Apr 2021
AlignMixup: Improving Representations By Interpolating Aligned Features Shashanka Venkataramanan Ewa Kijak Laurent Amsaleg Yannis Avrithis WSOL 33 61 0 29 Mar 2021
Essentials for Class Incremental Learning Sudhanshu Mittal Silvio Galesso Thomas Brox CLL 19 96 0 18 Feb 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 30 10 0 15 Feb 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Zou UQCV 31 67 0 11 Feb 2021
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Yogesh S Rawat M. Shah 241 509 0 15 Jan 2021
Self-Progressing Robust Training Minhao Cheng Pin-Yu Chen Sijia Liu Shiyu Chang Cho-Jui Hsieh Payel Das AAML VLM 29 9 0 22 Dec 2020
Uncertainty-Aware Deep Calibrated Salient Object Detection Jing Zhang Yuchao Dai Xin Yu Mehrtash Harandi Nick Barnes Richard I. Hartley UQCV EDL 26 6 0 10 Dec 2020
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting Hongxin Wei Lei Feng R. Wang Bo An NoLa 25 6 0 09 Dec 2020
PEP: Parameter Ensembling by Perturbation Alireza Mehrtash Purang Abolmaesumi Polina Golland Tina Kapur Demian Wassermann W. Wells 25 10 0 24 Oct 2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data Lingkai Kong Haoming Jiang Yuchen Zhuang Jie Lyu T. Zhao Chao Zhang OODD 27 26 0 22 Oct 2020
Learning Loss for Test-Time Augmentation Ildoo Kim Younghoon Kim Sungwoong Kim OOD 20 90 0 22 Oct 2020
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 32 63 0 19 Oct 2020
MixCo: Mix-up Contrastive Learning for Visual Representation Sungnyun Kim Gihun Lee Sangmin Bae Seyoung Yun SSL 112 80 0 13 Oct 2020
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 20 244 0 09 Oct 2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference Bang An Jie Lyu Zhenyi Wang Chunyuan Li Changwei Hu Fei Tan Ruiyi Zhang Yifan Hu Changyou Chen AAML 22 28 0 20 Sep 2020
Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization Yu-Ting Chang Qiaosong Wang Wei-Chih Hung Robinson Piramuthu Yi-Hsuan Tsai Ming-Hsuan Yang UQCV WSOL 22 34 0 03 Aug 2020
Remix: Rebalanced Mixup Hsin-Ping Chou Shih-Chieh Chang Jia-Yu Pan Wei Wei Da-Cheng Juan 36 231 0 08 Jul 2020
Improving Calibration through the Relationship with Adversarial Robustness Yao Qin Xuezhi Wang Alex Beutel Ed H. Chi AAML 40 25 0 29 Jun 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 22 9 0 12 Jun 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation Deepan Das Haley Massa Abhimanyu Kulkarni Theodoros Rekatsinas 21 18 0 06 Jun 2020
Self-Augmentation: Generalizing Deep Networks to Unseen Classes for Few-Shot Learning Jinhwan Seo Hong G Jung Seong-Whan Lee SSL 12 39 0 01 Apr 2020
Self-Supervised Learning for Domain Adaptation on Point-Clouds Idan Achituve Haggai Maron Gal Chechik 3DPC 35 160 0 29 Mar 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 30 6 0 22 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks Amir M. Rahimi Amirreza Shaban Ching-An Cheng Richard I. Hartley Byron Boots UQCV 14 68 0 15 Mar 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 56 444 0 21 Feb 2020
CAT: Customized Adversarial Training for Improved Robustness Minhao Cheng Qi Lei Pin-Yu Chen Inderjit Dhillon Cho-Jui Hsieh OOD AAML 27 114 0 17 Feb 2020
Estimating Uncertainty Intervals from Collaborating Networks Tianhui Zhou Yitong Li Yuan Wu David Carlson UQCV 30 15 0 12 Feb 2020
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 24 30 0 16 Dec 2019
Distance-Based Learning from Errors for Confidence Calibration Chen Xing Sercan Ö. Arik Zizhao Zhang Tomas Pfister FedML 23 39 0 03 Dec 2019
Entropic Out-of-Distribution Detection David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD UQCV 22 31 0 15 Aug 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 255 13,368 0 25 Aug 2014