OpenCodePapers

learning-with-noisy-labels-on-cifar-10n-worst

Learning with noisy labels
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PaperCodeAccuracy (mean)ModelNameReleaseDate
ProMix: Combating Label Noise via Maximizing Clean Sample Utility✓ Link96.16ProMix2022-07-21
PSSCL: A progressive sample selection framework with contrastive loss designed for noisy labels✓ Link95.12PSSCL2024-12-18
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels✓ Link93.65PGDF2021-12-02
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations✓ Link93.58ILL2023-05-22
Robust Training under Label Noise by Over-parameterization✓ Link93.24SOP+2022-02-28
DivideMix: Learning with Noisy Labels as Semi-supervised Learning✓ Link92.56Divide-Mix2020-02-18
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach✓ Link91.66CORES*2020-10-05
Early-Learning Regularization Prevents Memorization of Noisy Labels✓ Link91.09ELR+2020-06-30
Partial Label Supervision for Agnostic Generative Noisy Label Learning✓ Link86.99GNL2023-08-02
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels✓ Link85.36CAL2021-02-10
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels✓ Link83.83Co-Teaching2018-04-18
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach✓ Link83.60CORES2020-10-05
Early-Learning Regularization Prevents Memorization of Noisy Labels✓ Link83.58ELR2020-06-30
Combating noisy labels by agreement: A joint training method with co-regularization✓ Link83.37JoCoR2020-03-05
How does Disagreement Help Generalization against Label Corruption?✓ Link83.26Co-Teaching+2019-01-14
Understanding Generalized Label Smoothing when Learning with Noisy Labels✓ Link82.99Negative-LS2021-09-29
Does label smoothing mitigate label noise?82.76Positive-LS2020-03-05
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates✓ Link82.53Peer Loss2019-10-08
When Optimizing $f$-divergence is Robust with Label Noise✓ Link82.53F-div2020-11-07
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels✓ Link80.66GCE2018-05-20
Provably End-to-end Label-Noise Learning without Anchor Points✓ Link80.53VolMinNet2021-02-04
Are Anchor Points Really Indispensable in Label-Noise Learning?✓ Link80.48T-Revision2019-06-01
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach✓ Link79.79Forward-T2016-09-13
77.69CE
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach✓ Link77.61Backward-T2016-09-13
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