EricArazo / PseudoLabeling
Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"
☆153Updated 4 years ago
Alternatives and similar repositories for PseudoLabeling:
Users that are interested in PseudoLabeling are comparing it to the libraries listed below
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆126Updated 5 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆146Updated 4 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆185Updated 6 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆90Updated 4 years ago
- Meta-Learning based Noise-Tolerant Training☆123Updated 4 years ago
- ☆130Updated 2 years ago
- Code for Paper ''Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning'' [ICCV 2019]☆119Updated 4 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆78Updated 4 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆137Updated 4 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆222Updated 4 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 5 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆110Updated 6 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆186Updated 4 years ago
- Virtual Adversarial Training (VAT) implementation for PyTorch☆296Updated 6 years ago
- Pytorch implementation of Virtual Adversarial Training☆133Updated 5 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆118Updated last year
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆170Updated 3 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆48Updated 2 years ago
- Learning to Self-Train for Semi-Supervised Few-Shot☆93Updated 2 years ago
- "Learning to Discover Novel Visual Categories via Deep Transfer Clustering" by Kai Han, Andrea Vedaldi, Andrew Zisserman (ICCV 2019)☆162Updated 2 years ago
- Code for CVPR 2019 paper Label Propagation for Deep Semi-supervised Learning☆116Updated 4 years ago
- (NeurIPS 2020) Transductive Information Maximization for Few-Shot Learning https://arxiv.org/abs/2008.11297☆119Updated last year
- When Does Label Smoothing Help?_pytorch_implementationimp☆126Updated 5 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆82Updated 5 years ago
- Several SSL methods (Pi model, Mean Teacher) are implemented in pytorch☆82Updated 6 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆135Updated 7 months ago
- Pytorch Implementation of Domain Generalization Using a Mixture of Multiple Latent Domains☆99Updated 3 years ago
- Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)☆95Updated 3 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆104Updated 4 years ago