EvidentialMix: Learning with Combined Open-set and Closed-set Noisy
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EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels

11 November 2020

Vasileios Belagiannis

Papers citing "EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels"

13 / 13 papers shown

Title
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 105 1,029 0 18 Feb 2020
SELF: Learning to Filter Noisy Labels with Self-Ensembling Philipp Kratzer Marc Toussaint Thi Phuong Nhung Ngo T. Nguyen Jim Mainprice Thomas Brox NoLa 83 316 0 04 Oct 2019
NLNL: Negative Learning for Noisy Labels Youngdong Kim Junho Yim Juseung Yun Junmo Kim NoLa 49 276 0 19 Aug 2019
Robust Inference via Generative Classifiers for Handling Noisy Labels Kimin Lee Sukmin Yun Kibok Lee Honglak Lee Yue Liu Jinwoo Shin NoLa 82 139 0 31 Jan 2019
How does Disagreement Help Generalization against Label Corruption? Xingrui Yu Bo Han Jiangchao Yao Gang Niu Ivor W. Tsang Masashi Sugiyama NoLa 65 783 0 14 Jan 2019
Learning to Learn from Noisy Labeled Data Junnan Li Yongkang Wong Qi Zhao Mohan Kankanhalli NoLa 62 333 0 13 Dec 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 177 996 0 05 Jun 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 143 1,426 0 24 Mar 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 98 1,453 0 14 Dec 2017
A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets P. Chrabaszcz I. Loshchilov Frank Hutter SSeg OOD 161 647 0 27 Jul 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 339 4,626 0 10 Nov 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,184 0 16 Mar 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015