iBelieveCJM / Tricks-of-Semi-supervisedDeepLeanring-PytorchLinks
PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch
☆451Updated 2 years ago
Alternatives and similar repositories for Tricks-of-Semi-supervisedDeepLeanring-Pytorch
Users that are interested in Tricks-of-Semi-supervisedDeepLeanring-Pytorch are comparing it to the libraries listed below
Sorting:
- The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks☆338Updated 6 years ago
- Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"☆653Updated last year
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆559Updated 4 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆234Updated 3 years ago
- [NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning☆754Updated 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
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆682Updated 3 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆788Updated 2 years ago
- A curated list of long-tailed recognition resources.☆585Updated 2 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆507Updated 3 years ago
- This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 202…☆973Updated 3 years ago
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆800Updated last year
- The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition☆668Updated 2 years ago
- [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration☆473Updated 3 years ago
- [NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation …☆569Updated 11 months ago
- A collection of awesome things about mixed sample data augmentation☆132Updated 5 years ago
- Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019☆612Updated 3 years ago
- A PyTorch-based library for semi-supervised learning (NeurIPS'21)☆1,354Updated last year
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆187Updated 4 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆296Updated 2 years ago
- An efficient implicit semantic augmentation method, complementary to existing non-semantic techniques.☆590Updated 4 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆170Updated 4 years ago
- Unofficial PyTorch implementation of "Meta Pseudo Labels"☆387Updated last year
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- A Survey☆564Updated 2 years ago
- ☆570Updated 2 years ago
- PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"☆595Updated 2 months ago
- Code for paper "DeepEMD: Few-Shot Image Classification with Differentiable Earth Mover's Distance and Structured Classifiers", CVPR2020☆591Updated 2 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆223Updated 4 years ago
- A simple method to perform semi-supervised learning with limited data.☆1,166Updated 11 months ago