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A curated list of resources for Learning with Noisy Labels
Created
2019-07-17
284 commits to master branch, last one about a month ago
A curated (most recent) list of resources for Learning with Noisy Labels
Created
2021-04-14
134 commits to main branch, last one 3 months ago
Human annotated noisy labels for CIFAR-10 and CIFAR-100. The website of CIFAR-N is available at http://www.noisylabels.com/.
Created
2021-10-12
29 commits to main branch, last one about a year ago
[TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training
Created
2020-02-22
10 commits to master branch, last one 2 years ago
[ICML2022 Long Talk] Official Pytorch implementation of "To Smooth or Not? When Label Smoothing Meets Noisy Labels"
Created
2022-06-06
5 commits to master branch, last one about a year ago
[CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".
Created
2020-11-18
32 commits to master branch, last one 2 years ago
The official implementation of the ACM MM'2021 paper Co-learning: Learning from noisy labels with self-supervision.
Created
2021-03-17
8 commits to master branch, last one 2 years ago
[ICLR2021] Official Pytorch implementation of "When Optimizing f-Divergence is Robust with Label noise"
Created
2021-02-15
13 commits to main branch, last one 3 years ago
[ICLR 2024] SemiReward: A General Reward Model for Semi-supervised Learning
Created
2023-08-24
80 commits to main branch, last one 16 days ago
Learning to Split for Automatic Bias Detection
Created
2022-09-14
8 commits to main branch, last one about a year ago
(CVPR 2024) Pytorch implementation of “SURE: SUrvey REcipes for building reliable and robust deep networks”
Created
2024-03-01
22 commits to main branch, last one 12 days ago
ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"
Created
2021-01-31
6 commits to master branch, last one 2 years ago