bhanML / Co-teaching
NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
☆494Updated 3 years ago
Alternatives and similar repositories for Co-teaching:
Users that are interested in Co-teaching are comparing it to the libraries listed below
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆235Updated 3 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆221Updated 4 years ago
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆546Updated 4 years ago
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆649Updated 2 years ago
- Virtual Adversarial Training (VAT) implementation for PyTorch☆296Updated 5 years ago
- A curated list of long-tailed recognition resources.☆585Updated last year
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆353Updated 5 years ago
- This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 202…☆951Updated 3 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆185Updated 3 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆284Updated 3 years ago
- A Survey☆545Updated last year
- Code for reproducing Manifold Mixup results (ICML 2019)☆486Updated 8 months ago
- PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch☆445Updated last year
- Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks☆322Updated last year
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆126Updated 5 years ago
- Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"☆640Updated last year
- [NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation …☆560Updated 4 months ago
- Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)☆850Updated 2 years ago
- PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"☆574Updated 2 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 4 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆761Updated last year
- Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning, in ICCV 2021☆622Updated 3 years ago
- Variational Adversarial Active Learning (ICCV 2019)☆226Updated last year
- Meta-Learning based Noise-Tolerant Training☆123Updated 4 years ago
- Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach☆262Updated 6 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆290Updated last year
- Learning What and Where to Transfer (ICML 2019)☆251Updated 4 years ago
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆788Updated 9 months ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 5 years ago
- Implementation of the mixup training method☆464Updated 6 years ago