chenpf1025 / IDN
AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
☆36Updated 3 years ago
Alternatives and similar repositories for IDN:
Users that are interested in IDN are comparing it to the libraries listed below
- Meta Label Correction for Noisy Label Learning☆85Updated 2 years ago
- An update-to-date list for papers related with label-noise representation learning is here.☆89Updated 3 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 4 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆43Updated 2 years ago
- Official code for the paper "Meta Soft Label Generation for Noisy Labels" accepted at ICPR 2020.☆19Updated 4 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆76Updated 3 years ago
- This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.☆35Updated 3 years ago
- ☆16Updated last year
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆14Updated 3 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆91Updated 3 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆25Updated last year
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆47Updated last year
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆39Updated 3 years ago
- ☆29Updated 4 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆33Updated 4 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆64Updated 2 years ago
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- ☆14Updated last year
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆84Updated 5 years ago
- ☆29Updated 2 years ago
- [NeurIPS'20] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization☆20Updated 2 years ago
- A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.☆59Updated 3 years ago
- ☆28Updated 3 years ago
- Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".☆48Updated 4 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆138Updated 4 years ago
- ☆17Updated 3 years ago
- [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnab…☆44Updated 2 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆136Updated 8 months ago
- ☆32Updated 3 years ago
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆39Updated 3 years ago