xiaoboxia / T-Revision
NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?
☆97Updated 3 years ago
Alternatives and similar repositories for T-Revision:
Users that are interested in T-Revision are comparing it to the libraries listed below
- NeurIPS'2020: Part-dependent Label Noise: Towards Instance-dependent Label Noise☆59Updated 4 years ago
- TPAMI: Classification with noisy labels by importance reweighting.☆38Updated 5 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆75Updated 3 years ago
- ☆14Updated 2 years ago
- [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network☆19Updated 2 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆43Updated 2 years ago
- ☆23Updated 2 years ago
- ☆11Updated 3 years ago
- ☆30Updated 2 years ago
- source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training☆10Updated 2 years ago
- An update-to-date list for papers related with label-noise representation learning is here.☆90Updated 3 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆90Updated 2 years ago
- ☆14Updated last year
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆25Updated last year
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆46Updated last year
- ☆16Updated last year
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 3 years ago
- ☆29Updated 3 years ago
- Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".☆45Updated 4 years ago
- The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2…☆50Updated 4 years ago
- NeurIPS'2022: Pluralistic Image Completion with Gaussian Mixture Models☆13Updated 2 years ago
- A PyTorch-based library for On Learning Contrastive Representations for Learning With Noisy Labels (CVPR'22)☆40Updated 2 years ago
- Official code for the paper "Meta Soft Label Generation for Noisy Labels" accepted at ICPR 2020.☆19Updated 4 years ago
- ☆6Updated 3 years ago
- Source code for NeurIPS 2021 paper "TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation".☆9Updated 2 years ago
- [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"☆44Updated 3 years ago
- Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning☆43Updated last year
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆82Updated 5 years ago
- ☆46Updated last year