chenpf1025 / IDN
AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
☆35Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for IDN
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆42Updated 2 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 3 years ago
- Official code for the paper "Meta Soft Label Generation for Noisy Labels" accepted at ICPR 2020.☆19Updated 4 years ago
- Meta Label Correction for Noisy Label Learning☆81Updated 2 years ago
- An update-to-date list for papers related with label-noise representation learning is here.☆88Updated 3 years ago
- A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.☆56Updated 3 years ago
- ☆15Updated 11 months ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆75Updated 3 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆62Updated 2 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆91Updated 2 years ago
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆13Updated 3 years ago
- Source code for NeurIPS 2022 paper SoLar☆26Updated 11 months ago
- ☆29Updated last year
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆38Updated 2 years ago
- Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".☆46Updated 4 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆34Updated 3 years ago
- ☆12Updated last year
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- [NeurIPS'20] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization☆19Updated 2 years ago
- ☆16Updated 2 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆45Updated 10 months ago
- This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.☆32Updated 3 years ago
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆31Updated 3 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆24Updated last year
- ☆23Updated 2 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆83Updated 5 years ago
- Instance-Dependent Partial Label Learning(NIPS'21);Variational Label Enhancement for Instance-Dependent Partial Label Learning(TPAMI)☆25Updated 2 months ago
- Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…☆39Updated last year
- [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
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 2 years ago