gorkemalgan / deep_learning_with_noisy_labels_literature
This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.
☆236Updated 3 years ago
Related projects: ⓘ
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆486Updated 3 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆219Updated 4 years ago
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆529Updated 4 years ago
- PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch☆443Updated last year
- [NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation …☆560Updated last month
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆634Updated 2 years ago
- A curated list of long-tailed recognition resources.☆582Updated last year
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆280Updated 2 years ago
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆351Updated 5 years ago
- [ ECCV 2020 Spotlight ] Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets"☆358Updated 2 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆168Updated 3 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆181Updated 3 years ago
- "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…☆229Updated last year
- This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 202…☆938Updated 2 years ago
- Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"☆632Updated 10 months ago
- ☆447Updated last month
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆288Updated last year
- Virtual Adversarial Training (VAT) implementation for PyTorch☆296Updated 5 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆123Updated 4 years ago
- Variational Adversarial Active Learning (ICCV 2019)☆223Updated last year
- PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"☆562Updated 2 years ago
- A Survey☆532Updated last year
- A collection of awesome things about mixed sample data augmentation☆130Updated 4 years ago
- The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks☆335Updated 5 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆132Updated 2 months ago
- An update-to-date list for papers related with label-noise representation learning is here.☆88Updated 3 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆138Updated 5 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 3 years ago
- [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration☆468Updated 2 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆749Updated last year