An update-to-date list for papers related with label-noise representation learning is here.
☆91Aug 25, 2021Updated 4 years ago
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- Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020☆23Aug 23, 2020Updated 5 years ago
- A Survey☆572Feb 13, 2023Updated 3 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆236Sep 20, 2021Updated 4 years ago
- AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise☆35Jun 9, 2021Updated 4 years ago
- ☆27Aug 12, 2021Updated 4 years ago
- A curated list of resources for Learning with Noisy Labels☆2,721May 3, 2025Updated 10 months ago
- A curated (most recent) list of resources for Learning with Noisy Labels☆720Oct 18, 2024Updated last year
- This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.☆36Aug 29, 2021Updated 4 years ago
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆575Sep 14, 2020Updated 5 years ago
- [NeurIPS 2023] "Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation"☆11Oct 6, 2023Updated 2 years ago
- Regularly Truncated M-estimators for Learning with Noisy Labels☆11Apr 24, 2024Updated last year
- ☆10Jun 11, 2025Updated 8 months ago
- NeurIPS'2020: Part-dependent Label Noise: Towards Instance-dependent Label Noise☆61Dec 16, 2020Updated 5 years ago
- ICCV'2023: Holistic Label Correction for Noisy Multi-Label Classification☆13Oct 29, 2023Updated 2 years ago
- [NeurIPS 2023] Combating Bilateral Edge Noise for Robust Link Prediction☆13Nov 3, 2023Updated 2 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆299May 22, 2023Updated 2 years ago
- The released code for the paper: Pooling Architecture Search for Graph Classification, in CIKM 2021.☆26Jan 26, 2022Updated 4 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆78Jun 15, 2021Updated 4 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆519Aug 19, 2021Updated 4 years ago
- Continual/Lifelong/Incremental Learning☆12Jun 7, 2021Updated 4 years ago
- Uni-OVSeg is a weakly supervised open-vocabulary segmentation framework that leverages unpaired mask-text pairs.☆53Jun 11, 2024Updated last year
- code for our BMVC 2021 paper "HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification"☆15Oct 28, 2022Updated 3 years ago
- Survey on Robust Weakly Supervised Learning☆13Dec 23, 2021Updated 4 years ago
- ☆14Jan 7, 2023Updated 3 years ago
- NeurIPS 2022: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning☆18Mar 3, 2023Updated 3 years ago
- ☆30Jan 7, 2023Updated 3 years ago
- IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models☆59Jan 19, 2024Updated 2 years ago
- Meta-Learning based Noise-Tolerant Training☆123Aug 16, 2020Updated 5 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆17Dec 14, 2020Updated 5 years ago
- [ECCV2022] Motion Sensitive Contrastive Learning for Self-supervised Video Representation☆17Aug 12, 2022Updated 3 years ago
- Code for Deep Multimodal Clustering for Unsupervised Audiovisual Learning (CVPR2019)☆15May 27, 2020Updated 5 years ago
- 西电晨午晚检自动填报工具☆20Mar 10, 2021Updated 4 years ago
- StarNet: Targeted Computation for Object Detection in Point Clouds☆14Jan 28, 2020Updated 6 years ago
- Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization☆129May 1, 2025Updated 10 months ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Jul 5, 2024Updated last year
- ☆15Nov 21, 2020Updated 5 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆66Sep 15, 2022Updated 3 years ago
- [CIKM-2024] Official code for work "ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance"☆19Aug 14, 2024Updated last year
- ☆13May 19, 2021Updated 4 years ago