xiaoboxia / CDRLinks
ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
☆78Updated 4 years ago
Alternatives and similar repositories for CDR
Users that are interested in CDR are comparing it to the libraries listed below
Sorting:
- NeurIPS'2020: Part-dependent Label Noise: Towards Instance-dependent Label Noise☆60Updated 4 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆95Updated 3 years ago
- NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?☆100Updated 4 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆26Updated 2 years ago
- ☆14Updated 2 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆38Updated 4 years ago
- [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnab…☆45Updated 2 years ago
- A PyTorch implementation of the paper Targeted Supervised Contrastive Learning for Long-tailed Recognition☆103Updated 2 years ago
- Source code for NeurIPS 2022 paper SoLar☆29Updated last year
- [CVPR'22] Official Implementation of the CVPR 2022 paper "UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learnin…☆62Updated 11 months ago
- Awesome-open-world-learning☆26Updated 3 years ago
- Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".☆52Updated 5 years ago
- ☆24Updated 3 years ago
- Hao-Ning / MEIDTM-Instance-Dependent-Label-Noise-Learning-with-Manifold-Regularized-Transition-Matrix-Estimatiopytorch☆10Updated 3 years ago
- A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.☆61Updated 4 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆40Updated 3 years ago
- [NeurIPS'20] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization☆21Updated 3 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆34Updated 4 years ago
- ☆10Updated 3 years ago
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆15Updated 4 years ago
- [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network☆20Updated 3 years ago
- [ICLR 2022] Open-World Semi-Supervised Learning☆105Updated 3 years ago
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 5 years ago
- AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise☆35Updated 4 years ago
- Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"☆55Updated 3 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆49Updated last month
- This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2…☆101Updated 3 years ago
- ☆60Updated 3 years ago
- Exploiting Class Activation Value for Partial-Label Learning, ICLR 2022 (poster)☆14Updated 3 years ago
- ☆60Updated 2 years ago