WuYichen-97 / Learning-to-Purify-Noisy-Labels-via-Meta-Soft-Label-Corrector
[AAAI 21] Utilizing meta-learning to correct the noisy labels.
☆13Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for Learning-to-Purify-Noisy-Labels-via-Meta-Soft-Label-Corrector
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆90Updated 2 years ago
- Source code for NeurIPS 2022 paper SoLar☆26Updated 10 months ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆75Updated 3 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆38Updated 2 years ago
- Meta Label Correction for Noisy Label Learning☆81Updated 2 years ago
- Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"☆50Updated 2 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 3 years ago
- A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.☆57Updated 3 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆42Updated 2 years ago
- ☆29Updated last year
- A PyTorch-based library for On Learning Contrastive Representations for Learning With Noisy Labels (CVPR'22)☆40Updated 2 years ago
- [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnab…☆42Updated 2 years ago
- Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…☆39Updated last year
- ☆35Updated 2 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆24Updated last year
- Official code for the paper "Meta Soft Label Generation for Noisy Labels" accepted at ICPR 2020.☆18Updated 4 years ago
- Improving Calibration for Long-Tailed Recognition (CVPR2021)☆145Updated 2 years ago
- Instance-Dependent Partial Label Learning(NIPS'21);Variational Label Enhancement for Instance-Dependent Partial Label Learning(TPAMI)☆25Updated 2 months ago
- ☆29Updated 3 years ago
- ☆14Updated last year
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆62Updated 2 years ago
- Weakly Supervised Contrastive Learning☆39Updated 3 years ago
- Exploiting Domain-Specific Features to Enhance Domain Generalization (NeurIPS 2021).☆28Updated 2 years ago
- Official PyTorch Implementation of "CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning" (CVPR 20…☆51Updated 2 years ago
- [ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang☆63Updated 2 years ago
- ☆58Updated last year
- ☆51Updated 6 months ago
- Papers about long-tailed tasks☆88Updated last year
- AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise☆35Updated 3 years ago