EricArazo / PseudoLabelingLinks
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
Sorting:
- ☆129Updated 2 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆128Updated 5 years ago
- Meta-Learning based Noise-Tolerant Training☆126Updated 4 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 4 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 6 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 4 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆78Updated 4 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆48Updated 3 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆170Updated 4 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆223Updated 4 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆187Updated 4 years ago
- Code for CVPR 2019 paper Label Propagation for Deep Semi-supervised Learning☆116Updated 5 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆111Updated 6 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- "Learning to Discover Novel Visual Categories via Deep Transfer Clustering" by Kai Han, Andrea Vedaldi, Andrew Zisserman (ICCV 2019)☆166Updated 2 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Several SSL methods (Pi model, Mean Teacher) are implemented in pytorch☆82Updated 6 years ago
- Pytorch implementation of Virtual Adversarial Training☆134Updated 6 years ago
- Implementation of Adversarial Domain Adaptation with Domain Mixup (AAAI 2020 Oral).☆163Updated 5 years ago
- Code release for Discriminative Adversarial Domain Adaptation (AAAI2020).☆117Updated 5 years ago
- Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning☆94Updated 5 years ago
- Pytorch implementation of "A Simple Framework for Contrastive Learning of Visual Representations"☆82Updated last year
- Code for reproducing ICT (published in Neural Networks 2022, and in IJCAI 2019)☆149Updated 2 years ago
- A collection of awesome things about mixed sample data augmentation☆132Updated 5 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆125Updated 5 years ago
- Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆80Updated 5 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆138Updated last year
- Code for Paper ''Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning'' [ICCV 2019]☆118Updated 4 years ago