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The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration

30 November 2021

Jose Dolz

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Papers citing "The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration"

28 / 28 papers shown

Title
Beyond One-Hot Labels: Semantic Mixing for Model Calibration Haoyang Luo Linwei Tao Minjing Dong Chang Xu 118 0 0 18 Apr 2025
Adaptive Decision Boundary for Few-Shot Class-Incremental Learning Linhao Li Yongzhang Tan Siyuan Yang Hao Cheng Yongfeng Dong Liang Yang CLL 138 0 0 15 Apr 2025
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 262 1 0 25 Nov 2024
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 111 1 0 02 Nov 2023
Orthogonal Ensemble Networks for Biomedical Image Segmentation Agostina J. Larrazabal Cesar E. Martínez Jose Dolz Enzo Ferrante UQCV 63 22 0 22 May 2021
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking Xingchen Ma Matthew B. Blaschko 64 36 0 10 May 2021
Post-hoc Uncertainty Calibration for Domain Drift Scenarios Christian Tomani Sebastian Gruber Muhammed Ebrar Erdem Daniel Cremers Florian Buettner UQCV 170 67 0 20 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 667 41,369 0 22 Oct 2020
Local Temperature Scaling for Probability Calibration Zhipeng Ding Xu Han Peirong Liu Marc Niethammer 100 81 0 12 Aug 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 59 211 0 24 Jun 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 85 227 0 16 Mar 2020
Does label smoothing mitigate label noise? Michal Lukasik Srinadh Bhojanapalli A. Menon Surinder Kumar NoLa 184 351 0 05 Mar 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 83 465 0 21 Feb 2020
Confidence Calibration for Convolutional Neural Networks Using Structured Dropout Zhilu Zhang Adrian Dalca M. Sabuncu UQCV BDL 54 48 0 23 Jun 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 207 1,953 0 06 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 173 1,704 0 06 Jun 2019
Focal Loss for Dense Object Detection Nayeon Lee Priya Goyal Ross B. Girshick Kaiming He Piotr Dollár ObjD 124 2,998 0 07 Aug 2017
Rethinking Atrous Convolution for Semantic Image Segmentation Liang-Chieh Chen George Papandreou Florian Schroff Hartwig Adam SSeg 232 8,481 0 17 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,855 0 14 Jun 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 165 1,141 0 23 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,840 0 05 Dec 2016
DisturbLabel: Regularizing CNN on the Loss Layer Lingxi Xie Jingdong Wang Zhen Wei Meng Wang Qi Tian 131 252 0 30 Apr 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 60 257 0 15 Mar 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,322 0 10 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,412 0 02 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 831 9,345 0 06 Jun 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 130 946 0 18 Feb 2015
Network In Network Min Lin Qiang Chen Shuicheng Yan 294 6,283 0 16 Dec 2013