shengliu66 / ELRLinks
Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels
☆298Updated 2 years ago
Alternatives and similar repositories for ELR
Users that are interested in ELR are comparing it to the libraries listed below
Sorting:
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆572Updated 5 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Updated last year
- When Does Label Smoothing Help?_pytorch_implementationimp☆126Updated 5 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆130Updated 6 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆190Updated 4 years ago
- "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…☆235Updated 2 years ago
- ☆427Updated 4 years ago
- Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization☆128Updated 6 months ago
- [ICLR 2021 Spotlight] Code release for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."☆273Updated 2 years ago
- Improving Calibration for Long-Tailed Recognition (CVPR2021)☆150Updated 4 years ago
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆689Updated 3 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆236Updated 4 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆79Updated 5 years ago
- Pretrained SimCLRv2 models in Pytorch☆105Updated 5 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated 2 years ago
- Confidence-Aware Learning for Deep Neural Networks (ICML2020)☆74Updated 5 years ago
- PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results☆210Updated last year
- Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)☆546Updated last year
- PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"☆71Updated 4 years ago
- ☆130Updated 2 years ago
- NeurIPS 2020, Debiased Contrastive Learning☆283Updated 2 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 4 years ago
- Unofficial PyTorch implementation of "Meta Pseudo Labels"☆390Updated last year
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆171Updated 4 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆516Updated 4 years ago
- A collection of awesome things about mixed sample data augmentation☆132Updated 5 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆140Updated 6 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆155Updated 5 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆130Updated 4 years ago
- Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"☆185Updated 2 years ago