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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
- [NeurIPS 2023] "Combating Bilateral Edge Noise for Robust Link Prediction"☆11Nov 3, 2023Updated 2 years ago
- Codes for DATA: Differentiable ArchiTecture Approximation.☆11Jul 22, 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☆2,719May 3, 2025Updated 9 months ago
- [ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"☆18Jul 7, 2023Updated 2 years ago
- This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.☆36Aug 29, 2021Updated 4 years ago
- A curated (most recent) list of resources for Learning with Noisy Labels☆717Oct 18, 2024Updated last year
- Regularly Truncated M-estimators for Learning with Noisy Labels☆11Apr 24, 2024Updated last year
- The reproduce of paper "Continual Vision-Language Representation Learning with Off-Diagonal Information ".(Mod-X)☆10Oct 31, 2023Updated 2 years ago
- NeurIPS'2020: Part-dependent Label Noise: Towards Instance-dependent Label Noise☆61Dec 16, 2020Updated 5 years ago
- PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"☆71Mar 30, 2021Updated 4 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☆300May 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
- ICLR 2021: Noise against noise: stochastic label noise helps combat inherent label noise☆15May 1, 2021Updated 4 years ago
- Continual/Lifelong/Incremental Learning☆12Jun 7, 2021Updated 4 years ago
- source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training☆11Apr 28, 2022Updated 3 years ago
- 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
- NeurIPS 2022: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning☆18Mar 3, 2023Updated 2 years ago
- ☆14Jan 7, 2023Updated 3 years ago
- ☆30Jan 7, 2023Updated 3 years ago
- Meta-Learning based Noise-Tolerant Training☆123Aug 16, 2020Updated 5 years ago
- StarNet: Targeted Computation for Object Detection in Point Clouds☆14Jan 28, 2020Updated 6 years ago
- Code for Deep Multimodal Clustering for Unsupervised Audiovisual Learning (CVPR2019)☆15May 27, 2020Updated 5 years ago
- Noise of Web (NoW) is a challenging noisy correspondence learning (NCL) benchmark containing 100K image-text pairs for robust image-text …☆14Nov 20, 2025Updated 2 months ago
- [ECCV2022] Motion Sensitive Contrastive Learning for Self-supervised Video Representation☆17Aug 12, 2022Updated 3 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆17Dec 14, 2020Updated 5 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆127Oct 24, 2023Updated 2 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Jul 5, 2024Updated last year
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆66Sep 15, 2022Updated 3 years ago
- ☆13May 19, 2021Updated 4 years ago
- [CIKM-2024] Official code for work "ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance"☆19Aug 14, 2024Updated last year